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ORCIDJoseph Gonzalez 0001
Joseph E. Gonzalez
Person information
- affiliation: University of California at Berkeley, CA, USA
- affiliation (former): Carnegie Mellon University, Santa Clara, CA, USA
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2020 – today
- 2024
[c133]Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang:
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. ICLR 2024- [c132]Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph Gonzalez, Ion Stoica:
SLoRA: Scalable Serving of Thousands of LoRA Adapters. MLSys 2024 - [c131]Sarah Wooders, Shu Liu, Paras Jain, Xiangxi Mo, Joseph E. Gonzalez, Vincent Liu, Ion Stoica:
Cloudcast: High-Throughput, Cost-Aware Overlay Multicast in the Cloud. NSDI 2024: 281-296 - [c130]Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica:
Fairness in Serving Large Language Models. OSDI 2024: 965-988 - [c129]Sheng Shen, Shijia Yang, Tianjun Zhang, Bohan Zhai, Joseph E. Gonzalez, Kurt Keutzer, Trevor Darrell:
Multitask Vision-Language Prompt Tuning. WACV 2024: 5644-5655 - [c128]Suzanne Petryk, Spencer Whitehead, Joseph E. Gonzalez, Trevor Darrell, Anna Rohrbach, Marcus Rohrbach:
Simple Token-Level Confidence Improves Caption Correctness. WACV 2024: 5730-5740 - [i168]Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica:
Fairness in Serving Large Language Models. CoRR abs/2401.00588 (2024) - [i167]Jiezhi Yang, Khushi Desai, Charles Packer, Harshil Bhatia, Nicholas Rhinehart, Rowan McAllister, Joseph Gonzalez:
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting. CoRR abs/2401.18075 (2024) - [i166]Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica:
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. CoRR abs/2403.04132 (2024) - [i165]Shu Liu, Asim Biswal, Audrey Cheng, Xiangxi Mo, Shiyi Cao, Joseph E. Gonzalez, Ion Stoica, Matei Zaharia:
Optimizing LLM Queries in Relational Workloads. CoRR abs/2403.05821 (2024) - [i164]Tianjun Zhang, Shishir G. Patil, Naman Jain, Sheng Shen, Matei Zaharia, Ion Stoica, Joseph E. Gonzalez:
RAFT: Adapting Language Model to Domain Specific RAG. CoRR abs/2403.10131 (2024) - [i163]Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou, John F. Canny, Joseph E. Gonzalez, Trevor Darrell:
ALOHa: A New Measure for Hallucination in Captioning Models. CoRR abs/2404.02904 (2024) - [i162]Shishir G. Patil, Tianjun Zhang, Vivian Fang, Noppapon C., Roy Huang, Aaron Hao, Martin Casado, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica:
GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications. CoRR abs/2404.06921 (2024) - [i161]Sijun Tan, Xiuyu Li, Shishir G. Patil, Ziyang Wu, Tianjun Zhang, Kurt Keutzer, Joseph E. Gonzalez, Raluca Ada Popa:
LLoCO: Learning Long Contexts Offline. CoRR abs/2404.07979 (2024) - [i160]Michael Luo, Justin Wong, Brandon Trabucco, Yanping Huang, Joseph E. Gonzalez, Zhifeng Chen, Ruslan Salakhutdinov, Ion Stoica:
Stylus: Automatic Adapter Selection for Diffusion Models. CoRR abs/2404.18928 (2024) - [i159]Federico Mora, Justin Wong, Haley Lepe, Sahil Bhatia, Karim Elmaaroufi, George Varghese, Joseph E. Gonzalez, Elizabeth Polgreen, Sanjit A. Seshia:
Synthetic Programming Elicitation and Repair for Text-to-Code in Very Low-Resource Programming Languages. CoRR abs/2406.03636 (2024) - [i158]Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E. Gonzalez, Bin Cui:
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models. CoRR abs/2406.04271 (2024) - [i157]Tianle Li, Wei-Lin Chiang, Evan Frick, Lisa Dunlap, Tianhao Wu, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica:
From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline. CoRR abs/2406.11939 (2024) - [i156]Isaac Ong, Amjad Almahairi, Vincent Wu, Wei-Lin Chiang, Tianhao Wu, Joseph E. Gonzalez, M. Waleed Kadous, Ion Stoica:
RouteLLM: Learning to Route LLMs with Preference Data. CoRR abs/2406.18665 (2024) - 2023
- [j22]Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica:
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback. J. Mach. Learn. Res. 24: 53:1-53:45 (2023) - [j21]Robert Avram, Jeffrey E. Olgin, Zeeshan Ahmed, Louis Verreault-Julien, Alvin Wan, Joshua Barrios
, Sean Abreau, Derek Wan, Joseph E. Gonzalez, Jean-Claude Tardif, Derek Y. So, Krishan Soni, Geoffrey H. Tison:
CathAI: fully automated coronary angiography interpretation and stenosis estimation. npj Digit. Medicine 6 (2023) - [j20]Joseph E. Gonzalez, Yucheng Low:
The Story of GraphLab - From Scaling Machine Learning to Shaping Graph Systems Research. Proc. VLDB Endow. 16(12): 4138 (2023) - [j19]Sarah Wooders, Xiangxi Mo, Amit Narang, Kevin Lin, Ion Stoica, Joseph M. Hellerstein, Natacha Crooks, Joseph E. Gonzalez:
RALF: Accuracy-Aware Scheduling for Feature Store Maintenance. Proc. VLDB Endow. 17(3): 563-576 (2023) - [c127]Kevin Lin, Kyle Lo, Joseph Gonzalez, Dan Klein:
Decomposing Complex Queries for Tip-of-the-tongue Retrieval. EMNLP (Findings) 2023: 5521-5533 - [c126]David Chan, Suzanne Petryk, Joseph Gonzalez, Trevor Darrell, John F. Canny:
CLAIR: Evaluating Image Captions with Large Language Models. EMNLP 2023: 13638-13646 - [c125]Lisa Dunlap, Clara Mohri, Devin Guillory, Han Zhang, Trevor Darrell, Joseph E. Gonzalez, Aditi Raghunathan, Anna Rohrbach:
Using Language to Extend to Unseen Domains. ICLR 2023 - [c124]Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Spectral Decomposition Representation for Reinforcement Learning. ICLR 2023 - [c123]Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez:
TEMPERA: Test-Time Prompt Editing via Reinforcement Learning. ICLR 2023 - [c122]Tianjun Zhang, Fangchen Liu, Justin Wong, Pieter Abbeel, Joseph E. Gonzalez:
The Wisdom of Hindsight Makes Language Models Better Instruction Followers. ICML 2023: 41414-41428 - [c121]Jeffrey Ichnowski, Kaiyuan Chen, Karthik Dharmarajan, Simeon Adebola, Michael Danielczuk, Victor Mayoral Vilches, Nikhil Jha, Hugo Zhan, Edith LLontop, Derek Xu, Camilo Buscaron, John Kubiatowicz, Ion Stoica, Joseph Gonzalez, Ken Goldberg:
FogROS2: An Adaptive Platform for Cloud and Fog Robotics Using ROS 2. ICRA 2023: 5493-5500 - [c120]Peter Schafhalter, Sukrit Kalra, Le Xu, Joseph E. Gonzalez, Ion Stoica:
Leveraging Cloud Computing to Make Autonomous Vehicles Safer. IROS 2023: 5559-5566 - [c119]Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney:
Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data. KDD 2023: 3011-3021 - [c118]Yonghao Zhuang, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph Gonzalez, Ion Stoica, Hao Zhang, Hexu Zhao:
On Optimizing the Communication of Model Parallelism. MLSys 2023 - [c117]Lisa Dunlap, Alyssa Umino, Han Zhang, Jiezhi Yang, Joseph E. Gonzalez, Trevor Darrell:
Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation. NeurIPS 2023 - [c116]Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica:
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. NeurIPS 2023 - [c115]Paras Jain, Sam Kumar, Sarah Wooders, Shishir G. Patil, Joseph E. Gonzalez, Ion Stoica:
Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays. NSDI 2023: 1375-1389 - [c114]Romil Bhardwaj, Kirthevasan Kandasamy, Asim Biswal, Wenshuo Guo, Benjamin Hindman, Joseph Gonzalez, Michael I. Jordan, Ion Stoica:
Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback. OSDI 2023: 623-643 - [c113]Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica:
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving. OSDI 2023: 663-679 - [c112]Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, Ion Stoica:
Efficient Memory Management for Large Language Model Serving with PagedAttention. SOSP 2023: 611-626 - [c111]Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Energy-based Predictive Representations for Partially Observed Reinforcement Learning. UAI 2023: 2477-2487 - [i155]Tianjun Zhang, Fangchen Liu, Justin Wong, Pieter Abbeel, Joseph E. Gonzalez:
The Wisdom of Hindsight Makes Language Models Better Instruction Followers. CoRR abs/2302.05206 (2023) - [i154]Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica:
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving. CoRR abs/2302.11665 (2023) - [i153]Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang:
High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR abs/2303.06865 (2023) - [i152]Suzanne Petryk, Spencer Whitehead, Joseph E. Gonzalez, Trevor Darrell, Anna Rohrbach, Marcus Rohrbach:
Simple Token-Level Confidence Improves Caption Correctness. CoRR abs/2305.07021 (2023) - [i151]Kevin Lin, Kyle Lo, Joseph E. Gonzalez, Dan Klein:
Decomposing Complex Queries for Tip-of-the-tongue Retrieval. CoRR abs/2305.15053 (2023) - [i150]Shishir G. Patil, Tianjun Zhang, Xin Wang, Joseph E. Gonzalez:
Gorilla: Large Language Model Connected with Massive APIs. CoRR abs/2305.15334 (2023) - [i149]Lisa Dunlap, Alyssa Umino, Han Zhang, Jiezhi Yang, Joseph E. Gonzalez, Trevor Darrell:
Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation. CoRR abs/2305.16289 (2023) - [i148]Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica:
Judging LLM-as-a-judge with MT-Bench and Chatbot Arena. CoRR abs/2306.05685 (2023) - [i147]Peter Schafhalter, Sukrit Kalra, Le Xu, Joseph E. Gonzalez, Ion Stoica:
Leveraging Cloud Computing to Make Autonomous Vehicles Safer. CoRR abs/2308.03204 (2023) - [i146]Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, Ion Stoica:
Efficient Memory Management for Large Language Model Serving with PagedAttention. CoRR abs/2309.06180 (2023) - [i145]Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang:
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. CoRR abs/2309.11998 (2023) - [i144]Dacheng Li, Rulin Shao, Anze Xie, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang:
LightSeq: Sequence Level Parallelism for Distributed Training of Long Context Transformers. CoRR abs/2310.03294 (2023) - [i143]Rolando Garcia, Anusha Dandamudi, Gabriel Matute, Lehan Wan, Joseph Gonzalez, Joseph M. Hellerstein, Koushik Sen:
Multiversion Hindsight Logging for Continuous Training. CoRR abs/2310.07898 (2023) - [i142]Charles Packer, Vivian Fang, Shishir G. Patil, Kevin Lin, Sarah Wooders, Joseph E. Gonzalez:
MemGPT: Towards LLMs as Operating Systems. CoRR abs/2310.08560 (2023) - [i141]David Chan, Suzanne Petryk, Joseph E. Gonzalez, Trevor Darrell, John F. Canny:
CLAIR: Evaluating Image Captions with Large Language Models. CoRR abs/2310.12971 (2023) - [i140]Daniel Rothchild, Andrew S. Rosen, Eric Taw, Connie Robinson, Joseph E. Gonzalez, Aditi S. Krishnapriyan:
Investigating the Behavior of Diffusion Models for Accelerating Electronic Structure Calculations. CoRR abs/2311.01491 (2023) - [i139]Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph E. Gonzalez, Ion Stoica:
S-LoRA: Serving Thousands of Concurrent LoRA Adapters. CoRR abs/2311.03285 (2023) - [i138]Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, Joseph E. Gonzalez, Ion Stoica:
Rethinking Benchmark and Contamination for Language Models with Rephrased Samples. CoRR abs/2311.04850 (2023) - [i137]Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica:
LLM-Assisted Code Cleaning For Training Accurate Code Generators. CoRR abs/2311.14904 (2023) - [i136]Tsung-Han Wu, Long Lian, Joseph E. Gonzalez, Boyi Li, Trevor Darrell:
Self-correcting LLM-controlled Diffusion Models. CoRR abs/2311.16090 (2023) - [i135]Lisa Dunlap, Yuhui Zhang, Xiaohan Wang, Ruiqi Zhong, Trevor Darrell, Jacob Steinhardt, Joseph E. Gonzalez, Serena Yeung-Levy:
Describing Differences in Image Sets with Natural Language. CoRR abs/2312.02974 (2023) - [i134]Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Jeff Huang, Chuyue Sun, Cody Hao Yu, Shiyi Cao, Christos Kozyrakis, Ion Stoica, Joseph E. Gonzalez, Clark W. Barrett, Ying Sheng:
Efficiently Programming Large Language Models using SGLang. CoRR abs/2312.07104 (2023) - [i133]Tsung-Han Wu, Giscard Biamby, David Chan, Lisa Dunlap, Ritwik Gupta, Xudong Wang, Joseph E. Gonzalez, Trevor Darrell:
See, Say, and Segment: Teaching LMMs to Overcome False Premises. CoRR abs/2312.08366 (2023) - 2022
- [j18]David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. Computer 55(7): 18-28 (2022) - [j17]Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E. Gonzalez, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, Kurt Keutzer:
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. IEEE Trans. Neural Networks Learn. Syst. 33(2): 473-493 (2022) - [c110]Wenshuo Guo, Kirthevasan Kandasamy, Joseph Gonzalez, Michael I. Jordan, Ion Stoica:
Learning Competitive Equilibria in Exchange Economies with Bandit Feedback. AISTATS 2022: 6200-6224 - [c109]Charles Packer, Nicholas Rhinehart, Rowan Thomas McAllister, Matthew A. Wright, Xin Wang, Jeff He, Sergey Levine, Joseph E. Gonzalez:
Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty. CoRL 2022: 1607-1617 - [c108]Suzanne Petryk, Lisa Dunlap, Keyan Nasseri, Joseph Gonzalez, Trevor Darrell, Anna Rohrbach:
On Guiding Visual Attention with Language Specification. CVPR 2022: 18071-18081 - [c107]Paras Jain, Safeen Huda, Martin Maas, Joseph E. Gonzalez, Ion Stoica, Azalia Mirhoseini:
Learning to Design Accurate Deep Learning Accelerators with Inaccurate Multipliers. DATE 2022: 184-189 - [c106]Spencer Whitehead, Suzanne Petryk, Vedaad Shakib, Joseph Gonzalez, Trevor Darrell, Anna Rohrbach, Marcus Rohrbach:
Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly. ECCV (36) 2022: 148-166 - [c105]Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal, Xiangxi Mo, Sukrit Kalra, Peter Schafhalter, Eric Leong, Xin Wang, Bharathan Balaji, Joseph Gonzalez, Ion Stoica:
Context-Aware Streaming Perception in Dynamic Environments. ECCV (38) 2022: 621-638 - [c104]Ionel Gog, Sukrit Kalra, Peter Schafhalter, Joseph E. Gonzalez, Ion Stoica:
D3: a dynamic deadline-driven approach for building autonomous vehicles. EuroSys 2022: 453-471 - [c103]Bichen Wu, Ruizhe Cheng, Peizhao Zhang, Tianren Gao, Joseph E. Gonzalez, Peter Vajda:
Data Efficient Language-Supervised Zero-Shot Recognition with Optimal Transport Distillation. ICLR 2022 - [c102]Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez:
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. ICLR 2022 - [c101]Shishir G. Patil, Paras Jain, Prabal Dutta, Ion Stoica, Joseph Gonzalez:
POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging. ICML 2022: 17573-17583 - [c100]Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Prateek Mittal, Kannan Ramchandran, Joseph Gonzalez:
Neurotoxin: Durable Backdoors in Federated Learning. ICML 2022: 26429-26446 - [c99]Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai:
Making Linear MDPs Practical via Contrastive Representation Learning. ICML 2022: 26447-26466 - [c98]Brijen Thananjeyan, Justin Kerr, Huang Huang, Joseph E. Gonzalez, Ken Goldberg:
All You Need is LUV: Unsupervised Collection of Labeled Images Using UV-Fluorescent Markings. IROS 2022: 3241-3248 - [c97]Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica:
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. OSDI 2022: 559-578 - [c96]Vainavi Viswanath, Kaushik Shivakumar, Justin Kerr, Brijen Thananjeyan, Ellen R. Novoseller, Jeffrey Ichnowski, Alejandro Escontrela, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg:
Autonomously Untangling Long Cables. Robotics: Science and Systems 2022 - [c95]Sam Lau, Deborah Nolan, Joseph Gonzalez, Philip J. Guo:
How Computer Science and Statistics Instructors Approach Data Science Pedagogy Differently: Three Case Studies. SIGCSE (1) 2022: 29-35 - [i132]Zhanghao Wu, Paras Jain, Matthew A. Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica:
Representing Long-Range Context for Graph Neural Networks with Global Attention. CoRR abs/2201.08821 (2022) - [i131]Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica:
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. CoRR abs/2201.12023 (2022) - [i130]Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney:
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data. CoRR abs/2202.02842 (2022) - [i129]Suzanne Petryk, Lisa Dunlap, Keyan Nasseri, Joseph Gonzalez, Trevor Darrell, Anna Rohrbach:
On Guiding Visual Attention with Language Specification. CoRR abs/2202.08926 (2022) - [i128]Brijen Thananjeyan, Justin Kerr, Huang Huang, Joseph E. Gonzalez, Ken Goldberg:
All You Need is LUV: Unsupervised Collection of Labeled Images using Invisible UV Fluorescent Indicators. CoRR abs/2203.04566 (2022) - [i127]David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. CoRR abs/2204.05149 (2022) - [i126]Spencer Whitehead, Suzanne Petryk, Vedaad Shakib, Joseph Gonzalez, Trevor Darrell, Anna Rohrbach, Marcus Rohrbach:
Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly. CoRR abs/2204.13631 (2022) - [i125]Sarah E. Chasins, Alvin Cheung, Natacha Crooks, Ali Ghodsi, Ken Goldberg, Joseph E. Gonzalez, Joseph M. Hellerstein, Michael I. Jordan, Anthony D. Joseph, Michael W. Mahoney, Aditya G. Parameswaran, David A. Patterson, Raluca Ada Popa, Koushik Sen, Scott Shenker, Dawn Song, Ion Stoica:
The Sky Above The Clouds. CoRR abs/2205.07147 (2022) - [i124]Jeffrey Ichnowski, Kaiyuan Chen, Karthik Dharmarajan, Simeon Adebola, Michael Danielczuk, Victor Mayoral Vilches, Hugo Zhan, Derek Xu, Ramtin Ghassemi, John Kubiatowicz, Ion Stoica, Joseph Gonzalez, Ken Goldberg:
FogROS 2: An Adaptive and Extensible Platform for Cloud and Fog Robotics Using ROS 2. CoRR abs/2205.09778 (2022) - [i123]Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Joseph E. Gonzalez, Kannan Ramchandran, Prateek Mittal:
Neurotoxin: Durable Backdoors in Federated Learning. CoRR abs/2206.10341 (2022) - [i122]Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Making Linear MDPs Practical via Contrastive Representation Learning. CoRR abs/2207.07150 (2022) - [i121]Shishir G. Patil, Paras Jain, Prabal Dutta, Ion Stoica, Joseph E. Gonzalez:
POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging. CoRR abs/2207.07697 (2022) - [i120]Vainavi Viswanath, Kaushik Shivakumar, Justin Kerr, Brijen Thananjeyan, Ellen R. Novoseller, Jeffrey Ichnowski, Alejandro Escontrela, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg:
Autonomously Untangling Long Cables. CoRR abs/2207.07813 (2022) - [i119]Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal, Xiangxi Mo, Sukrit Kalra, Peter Schafhalter, Eric Leong, Xin Wang, Bharathan Balaji, Joseph Gonzalez, Ion Stoica:
Context-Aware Streaming Perception in Dynamic Environments. CoRR abs/2208.07479 (2022) - [i118]Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Spectral Decomposition Representation for Reinforcement Learning. CoRR abs/2208.09515 (2022) - [i117]Kevin Miao, Akash Gokul, Raghav Singh, Suzanne Petryk, Joseph Gonzalez, Kurt Keutzer, Trevor Darrell, Colorado Reed:
Prior Knowledge-Guided Attention in Self-Supervised Vision Transformers. CoRR abs/2209.03745 (2022) - [i116]Paras Jain, Sam Kumar, Sarah Wooders, Shishir G. Patil, Joseph E. Gonzalez, Ion Stoica:
Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays. CoRR abs/2210.07259 (2022) - [i115]Lisa Dunlap, Clara Mohri, Devin Guillory, Han Zhang, Trevor Darrell, Joseph E. Gonzalez, Aditi Raghunathan, Anna Rohrbach:
Using Language to Extend to Unseen Domains. CoRR abs/2210.09520 (2022) - [i114]Yonghao Zhuang, Hexu Zhao, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez, Ion Stoica, Hao Zhang:
On Optimizing the Communication of Model Parallelism. CoRR abs/2211.05322 (2022) - [i113]Sheng Shen, Shijia Yang, Tianjun Zhang, Bohan Zhai, Joseph E. Gonzalez, Kurt Keutzer, Trevor Darrell:
Multitask Vision-Language Prompt Tuning. CoRR abs/2211.11720 (2022) - [i112]Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez:
TEMPERA: Test-Time Prompting via Reinforcement Learning. CoRR abs/2211.11890 (2022) - [i111]Nathan Pemberton, Anton Zabreyko, Zhoujie Ding, Randy H. Katz, Joseph Gonzalez:
Kernel-as-a-Service: A Serverless Interface to GPUs. CoRR abs/2212.08146 (2022) - 2021
- [j16]Johann Schleier-Smith, Vikram Sreekanti, Anurag Khandelwal, João Carreira, Neeraja Jayant Yadwadkar, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica, David A. Patterson:
What serverless computing is and should become: the next phase of cloud computing. Commun. ACM 64(5): 76-84 (2021) - [j15]Doris Xin, Devin Petersohn, Dixin Tang, Yifan Wu, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time. IEEE Data Eng. Bull. 44(1): 66-78 (2021) - [j14]Devin Petersohn, Dixin Tang, Rehan Sohail Durrani, Areg Melik-Adamyan, Joseph Gonzalez, Anthony D. Joseph, Aditya G. Parameswaran:
Flexible Rule-Based Decomposition and Metadata Independence in Modin: A Parallel Dataframe System. Proc. VLDB Endow. 15(3): 739-751 (2021) - [j13]Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg:
Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones. IEEE Robotics Autom. Lett. 6(3): 4915-4922 (2021) - [c94]Zhengming Zhang, Yaoqing Yang, Zhewei Yao, Yujun Yan, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models. IEEE BigData 2021: 1214-1225 - [c93]Kaiyuan Chen, Yafei Liang, Nikhil Jha, Jeffrey Ichnowski, Michael Danielczuk, Joseph Gonzalez, John Kubiatowicz, Ken Goldberg:
FogROS: An Adaptive Framework for Automating Fog Robotics Deployment. CASE 2021: 2035-2042 - [c92]Lisa Dunlap, Kirthevasan Kandasamy, Ujval Misra, Richard Liaw, Michael I. Jordan, Ion Stoica, Joseph E. Gonzalez:
Elastic Hyperparameter Tuning on the Cloud. SoCC 2021: 33-46 - [c91]Albert Wilcox, Ashwin Balakrishna, Brijen Thananjeyan, Joseph E. Gonzalez, Ken Goldberg:
LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Sparse Reward Iterative Tasks. CoRL 2021: 959-969 - [c90]Ruizhe Cheng, Bichen Wu, Peizhao Zhang, Peter Vajda, Joseph E. Gonzalez:
Data-Efficient Language-Supervised Zero-Shot Learning With Self-Distillation. CVPR Workshops 2021: 3119-3124 - [c89]Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez:
FBNetV3: Joint Architecture-Recipe Search Using Predictor Pretraining. CVPR 2021: 16276-16285 - [c88]Yu Gai, Paras Jain, Wendi Zhang, Joseph Gonzalez, Dawn Song, Ion Stoica:
Grounded Graph Decoding improves Compositional Generalization in Question Answering. EMNLP (Findings) 2021: 1829-1838 - [c87]Paras Jain, Ajay Jain, Tianjun Zhang, Pieter Abbeel, Joseph Gonzalez, Ion Stoica:
Contrastive Code Representation Learning. EMNLP (1) 2021: 5954-5971 - [c86]Ujval Misra, Richard Liaw, Lisa Dunlap, Romil Bhardwaj, Kirthevasan Kandasamy, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
RubberBand: cloud-based hyperparameter tuning. EuroSys 2021: 327-342 - [c85]Nathan Pemberton, Johann Schleier-Smith, Joseph E. Gonzalez:
The RESTless cloud. HotOS 2021: 49-57 - [c84]Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Zhicheng Yan, Masayoshi Tomizuka, Joseph Gonzalez, Kurt Keutzer, Peter Vajda:
Visual Transformers: Where Do Transformers Really Belong in Vision Models? ICCV 2021: 579-589 - [c83]Xin Wang, Thomas E. Huang, Benlin Liu, Fisher Yu, Xiaolong Wang, Joseph E. Gonzalez, Trevor Darrell:
Robust Object Detection via Instance-Level Temporal Cycle Confusion. ICCV 2021: 9123-9132 - [c82]Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E. Gonzalez, Marcus Rohrbach, Trevor Darrell:
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting. ICLR 2021 - [c81]Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez:
NBDT: Neural-Backed Decision Tree. ICLR 2021 - [c80]Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph Gonzalez:
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. ICML 2021: 1803-1813 - [c79]Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph Gonzalez:
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism. ICML 2021: 10236-10246 - [c78]Samuel Paradis, Minho Hwang, Brijen Thananjeyan, Jeffrey Ichnowski, Daniel Seita, Danyal Fer, Thomas Low, Joseph E. Gonzalez, Ken Goldberg:
Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation. ICRA 2021: 7166-7173 - [c77]Raghav Anand, Jeffrey Ichnowski, Chenggang Wu, Joseph M. Hellerstein, Joseph E. Gonzalez, Ken Goldberg:
Serverless Multi-Query Motion Planning for Fog Robotics. ICRA 2021: 7457-7463 - [c76]Ionel Gog, Sukrit Kalra, Peter Schafhalter, Matthew A. Wright, Joseph E. Gonzalez, Ion Stoica:
Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles. ICRA 2021: 8806-8813 - [c75]Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Daniel Seita, Jennifer Grannen, Minho Hwang, Ryan Hoque, Joseph E. Gonzalez, Nawid Jamali, Katsu Yamane, Soshi Iba, Ken Goldberg:
Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics. ICRA 2021: 11515-11522 - [c74]Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine:
Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models. ICRA 2021: 13663-13669 - [c73]Vainavi Viswanath, Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Ellen R. Novoseller, Jeffrey Ichnowski, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg:
Disentangling Dense Multi-Cable Knots. IROS 2021: 3731-3738 - [c72]Guanhua Wang, Zhuang Liu, Brandon Hsieh, Siyuan Zhuang, Joseph Gonzalez, Trevor Darrell, Ion Stoica:
sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data. MLSys 2021 - [c71]Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian:
Learning Space Partitions for Path Planning. NeurIPS 2021: 378-391 - [c70]Charles Packer, Pieter Abbeel, Joseph E. Gonzalez:
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL. NeurIPS 2021: 2466-2477 - [c69]Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Joseph E. Gonzalez, Ion Stoica:
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem. NeurIPS 2021: 5506-5517 - [c68]Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, Stuart Russell:
MADE: Exploration via Maximizing Deviation from Explored Regions. NeurIPS 2021: 9663-9680 - [c67]Zhanghao Wu, Paras Jain, Matthew A. Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica:
Representing Long-Range Context for Graph Neural Networks with Global Attention. NeurIPS 2021: 13266-13279 - [c66]Yaoqing Yang, Liam Hodgkinson, Ryan Theisen, Joe Zou, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Taxonomizing local versus global structure in neural network loss landscapes. NeurIPS 2021: 18722-18733 - [c65]Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg:
Accelerating Quadratic Optimization with Reinforcement Learning. NeurIPS 2021: 21043-21055 - [c64]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
NovelD: A Simple yet Effective Exploration Criterion. NeurIPS 2021: 25217-25230 - [c63]Lianmin Zheng, Ruochen Liu, Junru Shao, Tianqi Chen, Joseph Gonzalez, Ion Stoica, Ameer Haj-Ali:
TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers. NeurIPS Datasets and Benchmarks 2021 - [c62]Anand Padmanabha Iyer, Qifan Pu, Kishan Patel, Joseph E. Gonzalez, Ion Stoica:
TEGRA: Efficient Ad-Hoc Analytics on Evolving Graphs. NSDI 2021: 337-355 - [c61]Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Jeffrey Ichnowski, Ellen R. Novoseller, Minho Hwang, Michael Laskey, Joseph Gonzalez, Ken Goldberg:
Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies. Robotics: Science and Systems 2021 - [c60]Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Joseph E. Gonzalez, Aaron D. Ames, Ken Goldberg:
ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions. WAFR 2021: 1-17 - [i110]Doris Xin, Devin Petersohn, Dixin Tang, Yifan Wu, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time. CoRR abs/2103.02145 (2021) - [i109]Ionel Gog, Sukrit Kalra, Peter Schafhalter, Matthew A. Wright, Joseph E. Gonzalez, Ion Stoica:
Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles. CoRR abs/2104.07830 (2021) - [i108]Xin Wang, Thomas E. Huang, Benlin Liu, Fisher Yu, Xiaolong Wang, Joseph E. Gonzalez, Trevor Darrell:
Robust Object Detection via Instance-Level Temporal Cycle Confusion. CoRR abs/2104.08381 (2021) - [i107]Ruizhe Cheng, Bichen Wu, Peizhao Zhang, Peter Vajda, Joseph E. Gonzalez:
Data-Efficient Language-Supervised Zero-Shot Learning with Self-Distillation. CoRR abs/2104.08945 (2021) - [i106]David A. Patterson, Joseph Gonzalez, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
Carbon Emissions and Large Neural Network Training. CoRR abs/2104.10350 (2021) - [i105]Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A. Wright, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine:
Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models. CoRR abs/2104.10558 (2021) - [i104]Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph E. Gonzalez:
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. CoRR abs/2104.14129 (2021) - [i103]Matthew A. Wright, Joseph E. Gonzalez:
Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines. CoRR abs/2106.01506 (2021) - [i102]Vainavi Viswanath, Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Ellen R. Novoseller, Jeffrey Ichnowski, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg:
Disentangling Dense Multi-Cable Knots. CoRR abs/2106.02252 (2021) - [i101]Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph E. Gonzalez:
PAC Best Arm Identification Under a Deadline. CoRR abs/2106.03221 (2021) - [i100]Wenshuo Guo, Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica:
Online Learning of Competitive Equilibria in Exchange Economies. CoRR abs/2106.06616 (2021) - [i99]Robert Avram, Jeffrey E. Olgin, Alvin Wan, Zeeshan Ahmed, Louis Verreault-Julien, Sean Abreau, Derek Wan, Joseph E. Gonzalez, Derek Y. So, Krishan Soni, Geoffrey H. Tison:
CathAI: Fully Automated Interpretation of Coronary Angiograms Using Neural Networks. CoRR abs/2106.07708 (2021) - [i98]Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph Gonzalez, Stuart Russell:
MADE: Exploration via Maximizing Deviation from Explored Regions. CoRR abs/2106.10268 (2021) - [i97]Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian:
Learning Space Partitions for Path Planning. CoRR abs/2106.10544 (2021) - [i96]Albert Wilcox, Ashwin Balakrishna, Brijen Thananjeyan, Joseph E. Gonzalez, Ken Goldberg:
LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Iterative Tasks. CoRR abs/2107.04775 (2021) - [i95]Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Jeffrey Ichnowski, Ellen R. Novoseller, Minho Hwang, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg:
Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies. CoRR abs/2107.08942 (2021) - [i94]Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg:
Accelerating Quadratic Optimization with Reinforcement Learning. CoRR abs/2107.10847 (2021) - [i93]Yaoqing Yang, Liam Hodgkinson, Ryan Theisen, Joe Zou, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Taxonomizing local versus global structure in neural network loss landscapes. CoRR abs/2107.11228 (2021) - [i92]Daniel Rothchild, Alex Tamkin, Julie Yu, Ujval Misra, Joseph Gonzalez:
C5T5: Controllable Generation of Organic Molecules with Transformers. CoRR abs/2108.10307 (2021) - [i91]Kaiyuan Chen, Yafei Liang, Nikhil Jha, Jeffrey Ichnowski, Michael Danielczuk, Joseph Gonzalez, John Kubiatowicz, Ken Goldberg:
FogROS: An Adaptive Framework for Automating Fog Robotics Deployment. CoRR abs/2108.11355 (2021) - [i90]Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez:
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. CoRR abs/2110.12080 (2021) - [i89]Yu Gai, Paras Jain, Wendi Zhang, Joseph E. Gonzalez, Dawn Song, Ion Stoica:
Grounded Graph Decoding Improves Compositional Generalization in Question Answering. CoRR abs/2111.03642 (2021) - [i88]Charles Packer, Pieter Abbeel, Joseph E. Gonzalez:
Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL. CoRR abs/2112.00901 (2021) - [i87]Alan Pham, Eunice Chan, Vikranth Srivatsa, Dhruba Ghosh, Yaoqing Yang, Yaodong Yu, Ruiqi Zhong, Joseph E. Gonzalez, Jacob Steinhardt:
The Effect of Model Size on Worst-Group Generalization. CoRR abs/2112.04094 (2021) - [i86]Bichen Wu, Ruizhe Cheng, Peizhao Zhang, Peter Vajda, Joseph E. Gonzalez:
Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillation. CoRR abs/2112.09445 (2021) - 2020
- [j12]Joseph Gonzalez:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 43(2): 2-3 (2020) - [j11]David E. Culler, Prabal Dutta, Gabe Fierro, Joseph E. Gonzalez, Nathan Pemberton, Johann Schleier-Smith, Kalyanaraman Shankari, Alvin Wan, Thomas Zachariah:
CoVista: A Unified View on Privacy Sensitive Mobile Contact Tracing. IEEE Data Eng. Bull. 43(2): 83-94 (2020) - [j10]Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Towards Scalable Dataframe Systems. Proc. VLDB Endow. 13(11): 2033-2046 (2020) - [j9]Vikram Sreekanti, Chenggang Wu, Xiayue Charles Lin, Johann Schleier-Smith, Joseph Gonzalez, Joseph M. Hellerstein, Alexey Tumanov:
Cloudburst: Stateful Functions-as-a-Service. Proc. VLDB Endow. 13(11): 2438-2452 (2020) - [j8]Rolando Garcia, Eric Liu, Vikram Sreekanti, Bobby Yan, Anusha Dandamudi, Joseph Gonzalez, Joseph M. Hellerstein, Koushik Sen:
Hindsight Logging for Model Training. Proc. VLDB Endow. 14(4): 682-693 (2020) - [j7]Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg:
Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks. IEEE Robotics Autom. Lett. 5(2): 3612-3619 (2020) - [j6]Ajay Kumar Tanwani, Raghav Anand, Joseph E. Gonzalez, Ken Goldberg:
RILaaS: Robot Inference and Learning as a Service. IEEE Robotics Autom. Lett. 5(3): 4423-4430 (2020) - [c59]Yaoqing Yang, Jichan Chung, Guanhua Wang, Vipul Gupta, Adarsh Karnati, Kenan Jiang, Ion Stoica, Joseph Gonzalez, Kannan Ramchandran:
Robust Class Parallelism - Error Resilient Parallel Inference with Low Communication Cost. ACSSC 2020: 1064-1065 - [c58]Vidit Saxena, Joakim Jaldén, Joseph Gonzalez:
Thompson Sampling for Linearly Constrained Bandits. AISTATS 2020: 1999-2009 - [c57]Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, Alexey Tumanov:
InferLine: latency-aware provisioning and scaling for prediction serving pipelines. SoCC 2020: 477-491 - [c56]Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna, Vainavi Viswanath, Michael Laskey, Joseph Gonzalez, Ken Goldberg:
Untangling Dense Knots by Learning Task-Relevant Keypoints. CoRL 2020: 782-800 - [c55]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CVPR 2020: 12962-12971 - [c54]Vikram Sreekanti, Chenggang Wu, Saurav Chhatrapati, Joseph E. Gonzalez, Joseph M. Hellerstein, Jose M. Faleiro:
A fault-tolerance shim for serverless computing. EuroSys 2020: 15:1-15:15 - [c53]Ankur Dave, Chester Leung, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Oblivious coopetitive analytics using hardware enclaves. EuroSys 2020: 39:1-39:17 - [c52]Xiayue Charles Lin, Joseph E. Gonzalez, Joseph M. Hellerstein:
Serverless Boom or Bust? An Analysis of Economic Incentives. HotCloud 2020 - [c51]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. ICML 2020: 8253-8265 - [c50]Xin Wang, Thomas E. Huang, Joseph Gonzalez, Trevor Darrell, Fisher Yu:
Frustratingly Simple Few-Shot Object Detection. ICML 2020: 9919-9928 - [c49]Harry Zhang, Jeffrey Ichnowski, Yahav Avigal, Joseph Gonzalez, Ion Stoica, Ken Goldberg:
Dex-Net AR: Distributed Deep Grasp Planning Using a Commodity Cellphone and Augmented Reality App. ICRA 2020: 552-558 - [c48]Jeffrey Ichnowski, William Lee, Victor Murta, Samuel Paradis, Ron Alterovitz, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg:
Fog Robotics Algorithms for Distributed Motion Planning Using Lambda Serverless Computing. ICRA 2020: 4232-4238 - [c47]Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Michael Laskey, Kevin Stone, Joseph E. Gonzalez, Ken Goldberg:
Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data. ICRA 2020: 9411-9418 - [c46]Samvit Jain, Xun Zhang, Yuhao Zhou, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Paramvir Bahl, Joseph Gonzalez:
Spatula: Efficient cross-camera video analytics on large camera networks. SEC 2020: 110-124 - [c45]Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph Gonzalez:
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. MLSys 2020 - [c44]Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez:
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks. NeurIPS 2020 - [c43]Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Boundary thickness and robustness in learning models. NeurIPS 2020 - [c42]Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica:
Ansor: Generating High-Performance Tensor Programs for Deep Learning. OSDI 2020: 863-879 - [i85]Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Towards Scalable Dataframe Systems. CoRR abs/2001.00888 (2020) - [i84]Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph Gonzalez, Ion Stoica, Alexey Tumanov:
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline. CoRR abs/2001.02338 (2020) - [i83]Vikram Sreekanti, Chenggang Wu, Xiayue Charles Lin, Johann Schleier-Smith, Jose M. Faleiro, Joseph E. Gonzalez, Joseph M. Hellerstein, Alexey Tumanov:
Cloudburst: Stateful Functions-as-a-Service. CoRR abs/2001.04592 (2020) - [i82]Bohan Zhai, Tianren Gao, Flora Xue, Daniel Rothchild, Bichen Wu, Joseph E. Gonzalez, Kurt Keutzer:
SqueezeWave: Extremely Lightweight Vocoders for On-device Speech Synthesis. CoRR abs/2001.05685 (2020) - [i81]Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez:
Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. CoRR abs/2002.11794 (2020) - [i80]Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Joseph E. Gonzalez, Aaron D. Ames, Ken Goldberg:
ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions. CoRR abs/2003.01410 (2020) - [i79]Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Michael Laskey, Kevin Stone, Joseph E. Gonzalez, Ken Goldberg:
Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data. CoRR abs/2003.01835 (2020) - [i78]Vikram Sreekanti, Chenggang Wu, Saurav Chhatrapati, Joseph E. Gonzalez, Joseph M. Hellerstein, Jose M. Faleiro:
A Fault-Tolerance Shim for Serverless Computing. CoRR abs/2003.06007 (2020) - [i77]Xin Wang, Thomas E. Huang, Trevor Darrell, Joseph E. Gonzalez, Fisher Yu:
Frustratingly Simple Few-Shot Object Detection. CoRR abs/2003.06957 (2020) - [i76]Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Daniel Seita, Jennifer Grannen, Minho Hwang, Ryan Hoque, Joseph E. Gonzalez, Nawid Jamali, Katsu Yamane, Soshi Iba, Ken Goldberg:
Learning to Smooth and Fold Real Fabric Using Dense Object Descriptors Trained on Synthetic Color Images. CoRR abs/2003.12698 (2020) - [i75]Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez:
NBDT: Neural-Backed Decision Trees. CoRR abs/2004.00221 (2020) - [i74]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CoRR abs/2004.05565 (2020) - [i73]Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica:
Mechanism Design with Bandit Feedback. CoRR abs/2004.08924 (2020) - [i72]Vidit Saxena, Joseph E. Gonzalez, Joakim Jaldén:
Thompson Sampling for Linearly Constrained Bandits. CoRR abs/2004.09258 (2020) - [i71]David E. Culler, Prabal Dutta, Gabe Fierro, Joseph E. Gonzalez, Nathan Pemberton, Johann Schleier-Smith, Kalyanaraman Shankari, Alvin Wan, Thomas Zachariah:
CoVista: A Unified View on Privacy Sensitive Mobile Contact Tracing Effort. CoRR abs/2005.13164 (2020) - [i70]Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez:
FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function. CoRR abs/2006.02049 (2020) - [i69]Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica:
Ansor : Generating High-Performance Tensor Programs for Deep Learning. CoRR abs/2006.06762 (2020) - [i68]Alvin Wan, Daniel Ho, Younjin Song, Henk Tillman, Sarah Adel Bargal, Joseph E. Gonzalez:
SegNBDT: Visual Decision Rules for Segmentation. CoRR abs/2006.06868 (2020) - [i67]Rolando Garcia, Eric Liu, Vikram Sreekanti, Bobby Yan, Anusha Dandamudi, Joseph E. Gonzalez, Joseph M. Hellerstein, Koushik Sen:
Hindsight Logging for Model Training. CoRR abs/2006.07357 (2020) - [i66]Mong H. Ng, Kaahan Radia, Jianfei Chen, Dequan Wang, Ionel Gog, Joseph E. Gonzalez:
BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud. CoRR abs/2006.11436 (2020) - [i65]Paras Jain, Ajay Jain, Tianjun Zhang, Pieter Abbeel, Joseph E. Gonzalez, Ion Stoica:
Contrastive Code Representation Learning. CoRR abs/2007.04973 (2020) - [i64]Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Boundary thickness and robustness in learning models. CoRR abs/2007.05086 (2020) - [i63]Vikram Sreekanti, Harikaran Subbaraj, Chenggang Wu, Joseph E. Gonzalez, Joseph M. Hellerstein:
Optimizing Prediction Serving on Low-Latency Serverless Dataflow. CoRR abs/2007.05832 (2020) - [i62]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. CoRR abs/2007.07682 (2020) - [i61]Zhengming Zhang, Zhewei Yao, Yaoqing Yang, Yujun Yan, Joseph E. Gonzalez, Michael W. Mahoney:
Benchmarking Semi-supervised Federated Learning. CoRR abs/2008.11364 (2020) - [i60]Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E. Gonzalez, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, Kurt Keutzer:
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. CoRR abs/2009.00155 (2020) - [i59]Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E. Gonzalez, Marcus Rohrbach, Trevor Darrell:
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting. CoRR abs/2010.01528 (2020) - [i58]Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Daniel Seita, Ryan Hoque, Joseph E. Gonzalez, Ken Goldberg:
MMGSD: Multi-Modal Gaussian Shape Descriptors for Correspondence Matching in 1D and 2D Deformable Objects. CoRR abs/2010.04339 (2020) - [i57]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
Multi-Agent Collaboration via Reward Attribution Decomposition. CoRR abs/2010.08531 (2020) - [i56]Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez:
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks. CoRR abs/2010.14298 (2020) - [i55]Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg:
Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones. CoRR abs/2010.15920 (2020) - [i54]Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph E. Gonzalez:
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism. CoRR abs/2011.00330 (2020) - [i53]Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna, Minho Hwang, Vainavi Viswanath, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg:
Untangling Dense Knots by Learning Task-Relevant Keypoints. CoRR abs/2011.04999 (2020) - [i52]Samuel Paradis, Minho Hwang, Brijen Thananjeyan, Jeffrey Ichnowski, Daniel Seita, Danyal Fer, Thomas Low, Joseph E. Gonzalez, Ken Goldberg:
Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation. CoRR abs/2011.06163 (2020) - [i51]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
BeBold: Exploration Beyond the Boundary of Explored Regions. CoRR abs/2012.08621 (2020) - [i50]Kirthevasan Kandasamy, Gur-Eyal Sela, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica:
Online Learning Demands in Max-min Fairness. CoRR abs/2012.08648 (2020)
2010 – 2019
- 2019
- [c41]Joseph M. Hellerstein, Jose M. Faleiro, Joseph Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, Chenggang Wu:
Serverless Computing: One Step Forward, Two Steps Back. CIDR 2019 - [c40]Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline. SoCC 2019: 61-73 - [c39]Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Felix Li, Arsh Zahed, Joseph E. Gonzalez, Ken Goldberg:
On-Policy Robot Imitation Learning from a Converging Supervisor. CoRL 2019: 24-41 - [c38]Xin Wang, Fisher Yu, Ruth Wang, Trevor Darrell, Joseph E. Gonzalez:
TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning. CVPR 2019: 1831-1840 - [c37]Samvit Jain, Xin Wang, Joseph E. Gonzalez:
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video. CVPR 2019: 8866-8875 - [c36]Zuxuan Wu, Xin Wang, Joseph Gonzalez, Tom Goldstein, Larry Davis:
ACE: Adapting to Changing Environments for Semantic Segmentation. ICCV 2019: 2121-2130 - [c35]Ajay Kumar Tanwani, Nitesh Mor, John Kubiatowicz, Joseph E. Gonzalez, Ken Goldberg:
A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering. ICRA 2019: 4559-4566 - [c34]Tianjun Zhang, Zhewei Yao, Amir Gholami, Joseph E. Gonzalez, Kurt Keutzer, Michael W. Mahoney, George Biros:
ANODEV2: A Coupled Neural ODE Framework. NeurIPS 2019: 5152-5162 - [c33]Vidit Saxena, Joakim Jaldén, Joseph E. Gonzalez, Mats Bengtsson, Hugo M. Tullberg, Ion Stoica:
Contextual Multi-Armed Bandits for Link Adaptation in Cellular Networks. NetAI@SIGCOMM 2019: 44-49 - [c32]Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Helen: Maliciously Secure Coopetitive Learning for Linear Models. IEEE Symposium on Security and Privacy 2019: 724-738 - [c31]Xin Wang, Fisher Yu, Lisa Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez:
Deep Mixture of Experts via Shallow Embedding. UAI 2019: 552-562 - [c30]Samvit Jain, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Joseph Gonzalez:
Scaling Video Analytics Systems to Large Camera Deployments. HotMobile 2019: 9-14 - [i49]Paras Jain, Xiangxi Mo, Ajay Jain, Harikaran Subbaraj, Rehan Sohail Durrani, Alexey Tumanov, Joseph Gonzalez, Ion Stoica:
Dynamic Space-Time Scheduling for GPU Inference. CoRR abs/1901.00041 (2019) - [i48]Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica:
The OoO VLIW JIT Compiler for GPU Inference. CoRR abs/1901.10008 (2019) - [i47]Eric Jonas, Johann Schleier-Smith, Vikram Sreekanti, Chia-Che Tsai, Anurag Khandelwal, Qifan Pu, Vaishaal Shankar, João Carreira, Karl Krauth, Neeraja Jayant Yadwadkar, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica, David A. Patterson:
Cloud Programming Simplified: A Berkeley View on Serverless Computing. CoRR abs/1902.03383 (2019) - [i46]Vidit Saxena, Joakim Jaldén, Joseph E. Gonzalez, Ion Stoica, Hugo M. Tullberg:
Constrained Thompson Sampling for Wireless Link Optimization. CoRR abs/1902.11102 (2019) - [i45]Ajay Kumar Tanwani, Nitesh Mor, John Kubiatowicz, Joseph E. Gonzalez, Ken Goldberg:
A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering. CoRR abs/1903.09589 (2019) - [i44]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i43]Xin Wang, Fisher Yu, Ruth Wang, Trevor Darrell, Joseph E. Gonzalez:
TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning. CoRR abs/1904.05967 (2019) - [i42]Zuxuan Wu, Xin Wang, Joseph E. Gonzalez, Tom Goldstein, Larry S. Davis:
ACE: Adapting to Changing Environments for Semantic Segmentation. CoRR abs/1904.06268 (2019) - [i41]Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg:
Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations. CoRR abs/1905.13402 (2019) - [i40]Tianjun Zhang, Zhewei Yao, Amir Gholami, Kurt Keutzer, Joseph Gonzalez, George Biros, Michael W. Mahoney:
ANODEV2: A Coupled Neural ODE Evolution Framework. CoRR abs/1906.04596 (2019) - [i39]Xin Wang, Fisher Yu, Trevor Darrell, Joseph E. Gonzalez:
Task-Aware Deep Sampling for Feature Generation. CoRR abs/1906.04854 (2019) - [i38]Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Arsh Zahed, Felix Li, Joseph E. Gonzalez, Ken Goldberg:
On-Policy Robot Imitation Learning from a Converging Supervisor. CoRR abs/1907.03423 (2019) - [i37]Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Helen: Maliciously Secure Coopetitive Learning for Linear Models. CoRR abs/1907.07212 (2019) - [i36]Ameer Haj-Ali, Nesreen K. Ahmed, Theodore L. Willke, Joseph Gonzalez, Krste Asanovic, Ion Stoica:
Deep Reinforcement Learning in System Optimization. CoRR abs/1908.01275 (2019) - [i35]Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph E. Gonzalez:
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. CoRR abs/1910.02653 (2019) - [i34]Tianyuan Zhang, Bichen Wu, Xin Wang, Joseph Gonzalez, Kurt Keutzer:
Domain-Aware Dynamic Networks. CoRR abs/1911.13237 (2019) - 2018
- [j5]Daniel Crankshaw, Joseph Gonzalez, Peter Bailis:
Research for practice: prediction-serving systems. Commun. ACM 61(8): 45-49 (2018) - [j4]Joseph E. Gonzalez:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 41(4): 4 (2018) - [c29]Bichen Wu, Alvin Wan, Xiangyu Yue, Peter H. Jin, Sicheng Zhao, Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, Kurt Keutzer:
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions. CVPR 2018: 9127-9135 - [c28]Samvit Jain, Joseph E. Gonzalez:
Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation. ECCV Workshops (4) 2018: 3-6 - [c27]Xin Wang, Fisher Yu, Zi-Yi Dou, Trevor Darrell, Joseph E. Gonzalez:
SkipNet: Learning Dynamic Routing in Convolutional Networks. ECCV (13) 2018: 420-436 - [c26]Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Ken Goldberg, Joseph Gonzalez, Michael I. Jordan, Ion Stoica:
RLlib: Abstractions for Distributed Reinforcement Learning. ICML 2018: 3059-3068 - [c25]Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Fisher Yu, Joseph E. Gonzalez:
IDK Cascades: Fast Deep Learning by Learning not to Overthink. UAI 2018: 580-590 - [i33]Vladimir Feinberg, Alvin Wan, Ion Stoica, Michael I. Jordan, Joseph E. Gonzalez, Sergey Levine:
Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning. CoRR abs/1803.00101 (2018) - [i32]Samvit Jain, Joseph E. Gonzalez:
Fast Semantic Segmentation on Video Using Motion Vector-Based Feature Interpolation. CoRR abs/1803.07742 (2018) - [i31]Sicheng Zhao, Bichen Wu, Joseph Gonzalez, Sanjit A. Seshia, Kurt Keutzer:
Unsupervised Domain Adaptation: from Simulation Engine to the RealWorld. CoRR abs/1803.09180 (2018) - [i30]Xin Wang, Fisher Yu, Ruth Wang, Yi-An Ma, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez:
Deep Mixture of Experts via Shallow Embedding. CoRR abs/1806.01531 (2018) - [i29]Richard Liaw, Eric Liang, Robert Nishihara, Philipp Moritz, Joseph E. Gonzalez, Ion Stoica:
Tune: A Research Platform for Distributed Model Selection and Training. CoRR abs/1807.05118 (2018) - [i28]Samvit Jain, Xin Wang, Joseph Gonzalez:
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video. CoRR abs/1807.06667 (2018) - [i27]Samvit Jain, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Joseph E. Gonzalez:
Scaling Video Analytics Systems to Large Camera Deployments. CoRR abs/1809.02318 (2018) - [i26]Samvit Jain, Joseph E. Gonzalez:
Inter-BMV: Interpolation with Block Motion Vectors for Fast Semantic Segmentation on Video. CoRR abs/1810.04047 (2018) - [i25]Samvit Jain, Junchen Jiang, Yuanchao Shu, Ganesh Ananthanarayanan, Joseph Gonzalez:
ReXCam: Resource-Efficient, Cross-Camera Video Analytics at Enterprise Scale. CoRR abs/1811.01268 (2018) - [i24]Noah Golmant, Nikita Vemuri, Zhewei Yao, Vladimir Feinberg, Amir Gholami, Kai Rothauge, Michael W. Mahoney, Joseph Gonzalez:
On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent. CoRR abs/1811.12941 (2018) - [i23]J. Weston Hughes, Taylor Sittler, Anthony D. Joseph, Jeffrey E. Olgin, Joseph E. Gonzalez, Geoffrey H. Tison:
Using Multitask Learning to Improve 12-Lead Electrocardiogram Classification. CoRR abs/1812.00497 (2018) - [i22]Daniel Crankshaw, Gur-Eyal Sela, Corey Zumar, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
InferLine: ML Inference Pipeline Composition Framework. CoRR abs/1812.01776 (2018) - [i21]Joseph M. Hellerstein, Jose M. Faleiro, Joseph E. Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, Chenggang Wu:
Serverless Computing: One Step Forward, Two Steps Back. CoRR abs/1812.03651 (2018) - 2017
- [c24]Francois Belletti, Evan Randall Sparks, Alexandre M. Bayen, Joseph Gonzalez:
Random projection design for scalable implicit smoothing of randomly observed stochastic processes. AISTATS 2017: 700-708 - [c23]Joseph M. Hellerstein, Vikram Sreekanti, Joseph E. Gonzalez, James Dalton, Akon Dey, Sreyashi Nag, Krishna Ramachandran, Sudhanshu Arora, Arka Bhattacharyya, Shirshanka Das, Mark Donsky, Gabriel Fierro, Chang She, Carl Steinbach, Venkat Subramanian, Eric Sun:
Ground: A Data Context Service. CIDR 2017 - [c22]Neeraja Jayant Yadwadkar, Bharath Hariharan, Joseph E. Gonzalez, Burton Smith, Randy H. Katz:
Selecting the best VM across multiple public clouds: a data-driven performance modeling approach. SoCC 2017: 452-465 - [c21]Wenting Zheng, Ankur Dave, Jethro G. Beekman, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Opaque: An Oblivious and Encrypted Distributed Analytics Platform. NSDI 2017: 283-298 - [c20]Daniel Crankshaw, Xin Wang, Giulio Zhou, Michael J. Franklin, Joseph E. Gonzalez, Ion Stoica:
Clipper: A Low-Latency Online Prediction Serving System. NSDI 2017: 613-627 - [i20]Xinghao Pan, Shivaram Venkataraman, Zizheng Tai, Joseph Gonzalez:
Hemingway: Modeling Distributed Optimization Algorithms. CoRR abs/1702.05865 (2017) - [i19]Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Joseph E. Gonzalez:
IDK Cascades: Fast Deep Learning by Learning not to Overthink. CoRR abs/1706.00885 (2017) - [i18]Richard Liaw, Sanjay Krishnan, Animesh Garg, Daniel Crankshaw, Joseph E. Gonzalez, Ken Goldberg:
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning. CoRR abs/1711.01503 (2017) - [i17]Bichen Wu, Alvin Wan, Xiangyu Yue, Peter H. Jin, Sicheng Zhao, Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, Kurt Keutzer:
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions. CoRR abs/1711.08141 (2017) - [i16]Xin Wang, Fisher Yu, Zi-Yi Dou, Joseph E. Gonzalez:
SkipNet: Learning Dynamic Routing in Convolutional Networks. CoRR abs/1711.09485 (2017) - [i15]Ion Stoica, Dawn Song, Raluca Ada Popa, David A. Patterson, Michael W. Mahoney, Randy H. Katz, Anthony D. Joseph, Michael I. Jordan, Joseph M. Hellerstein, Joseph E. Gonzalez, Ken Goldberg, Ali Ghodsi, David E. Culler, Pieter Abbeel:
A Berkeley View of Systems Challenges for AI. CoRR abs/1712.05855 (2017) - [i14]Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Joseph Gonzalez, Ken Goldberg, Ion Stoica:
Ray RLLib: A Composable and Scalable Reinforcement Learning Library. CoRR abs/1712.09381 (2017) - 2016
- [j3]Matei Zaharia, Reynold S. Xin, Patrick Wendell, Tathagata Das, Michael Armbrust, Ankur Dave, Xiangrui Meng, Josh Rosen, Shivaram Venkataraman, Michael J. Franklin, Ali Ghodsi, Joseph Gonzalez, Scott Shenker, Ion Stoica:
Apache Spark: a unified engine for big data processing. Commun. ACM 59(11): 56-65 (2016) - [j2]Neeraja Jayant Yadwadkar, Bharath Hariharan, Joseph E. Gonzalez, Randy Howard Katz:
Multi-Task Learning for Straggler Avoiding Predictive Job Scheduling. J. Mach. Learn. Res. 17: 106:1-106:37 (2016) - [c19]Ankur Dave, Alekh Jindal, Li Erran Li, Reynold Xin, Joseph Gonzalez, Matei Zaharia:
GraphFrames: an integrated API for mixing graph and relational queries. GRADES 2016: 2 - [i13]Francois W. Belletti, Evan Randall Sparks, Michael J. Franklin, Alexandre M. Bayen, Joseph E. Gonzalez:
Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies. CoRR abs/1603.03336 (2016) - [i12]Daniel Crankshaw, Xin Wang, Giulio Zhou, Michael J. Franklin, Joseph E. Gonzalez, Ion Stoica:
Clipper: A Low-Latency Online Prediction Serving System. CoRR abs/1612.03079 (2016) - 2015
- [c18]Veronika Strnadová-Neeley, Aydin Buluç, Jarrod Chapman, John R. Gilbert, Joseph Gonzalez, Leonid Oliker:
Efficient data reduction for large-scale genetic mapping. BCB 2015: 126-135 - [c17]Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan:
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox. CIDR 2015 - [c16]Neeraja Jayant Yadwadkar, Bharath Hariharan, Joseph Gonzalez, Randy H. Katz:
Faster Jobs in Distributed Data Processing using Multi-Task Learning. SDM 2015: 532-540 - [i11]Joseph E. Gonzalez, Peter Bailis, Michael I. Jordan, Michael J. Franklin, Joseph M. Hellerstein, Ali Ghodsi, Ion Stoica:
Asynchronous Complex Analytics in a Distributed Dataflow Architecture. CoRR abs/1510.07092 (2015) - 2014
- [c15]Veronika Strnadova, Aydin Buluç, Jarrod Chapman, John R. Gilbert, Joseph Gonzalez, Stefanie Jegelka, Daniel Rokhsar, Leonid Oliker:
Efficient and accurate clustering for large-scale genetic mapping. BIBM 2014: 3-10 - [c14]Tim Mattson, David A. Bader, Aydin Buluç, John R. Gilbert, Joseph Gonzalez, Jeremy Kepner:
GABB Introduction. IPDPS Workshops 2014: 1135-1137 - [c13]Xinghao Pan, Stefanie Jegelka, Joseph E. Gonzalez, Joseph K. Bradley, Michael I. Jordan:
Parallel Double Greedy Submodular Maximization. NIPS 2014: 118-126 - [c12]Joseph E. Gonzalez, Reynold S. Xin, Ankur Dave, Daniel Crankshaw, Michael J. Franklin, Ion Stoica:
GraphX: Graph Processing in a Distributed Dataflow Framework. OSDI 2014: 599-613 - [c11]Joseph E. Gonzalez:
From graphs to tables the design of scalable systems for graph analytics. WWW (Companion Volume) 2014: 1149-1150 - [i10]Reynold S. Xin, Daniel Crankshaw, Ankur Dave, Joseph E. Gonzalez, Michael J. Franklin, Ion Stoica:
GraphX: Unifying Data-Parallel and Graph-Parallel Analytics. CoRR abs/1402.2394 (2014) - [i9]Tim Mattson, David A. Bader, Jonathan W. Berry, Aydin Buluç, Jack J. Dongarra, Christos Faloutsos, John Feo, John R. Gilbert, Joseph Gonzalez, Bruce Hendrickson, Jeremy Kepner, Charles E. Leiserson, Andrew Lumsdaine, David A. Padua, Stephen W. Poole, Steven P. Reinhardt, Mike Stonebraker, Steve Wallach, Andrew Yoo:
Standards for Graph Algorithm Primitives. CoRR abs/1408.0393 (2014) - [i8]Yucheng Low, Joseph E. Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
GraphLab: A New Framework For Parallel Machine Learning. CoRR abs/1408.2041 (2014) - [i7]Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael I. Jordan:
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox. CoRR abs/1409.3809 (2014) - 2013
- [c10]Tim Mattson, David A. Bader, Jonathan W. Berry, Aydin Buluç, Jack J. Dongarra, Christos Faloutsos, John Feo, John R. Gilbert, Joseph Gonzalez, Bruce Hendrickson, Jeremy Kepner, Charles E. Leiserson, Andrew Lumsdaine, David A. Padua, Stephen Poole, Steven P. Reinhardt, Mike Stonebraker, Steve Wallach, Andrew Yoo:
Standards for graph algorithm primitives. HPEC 2013: 1-2 - [c9]Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
MLI: An API for Distributed Machine Learning. ICDM 2013: 1187-1192 - [c8]Xinghao Pan, Joseph E. Gonzalez, Stefanie Jegelka, Tamara Broderick, Michael I. Jordan:
Optimistic Concurrency Control for Distributed Unsupervised Learning. NIPS 2013: 1403-1411 - [c7]Reynold S. Xin, Joseph E. Gonzalez, Michael J. Franklin, Ion Stoica:
GraphX: a resilient distributed graph system on Spark. GRADES 2013: 2 - [i6]Xinghao Pan, Joseph E. Gonzalez, Stefanie Jegelka, Tamara Broderick, Michael I. Jordan:
Optimistic Concurrency Control for Distributed Unsupervised Learning. CoRR abs/1307.8049 (2013) - [i5]Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
MLI: An API for Distributed Machine Learning. CoRR abs/1310.5426 (2013) - 2012
- [j1]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
Distributed GraphLab: A Framework for Machine Learning in the Cloud. Proc. VLDB Endow. 5(8): 716-727 (2012) - [c6]Joseph E. Gonzalez, Yucheng Low, Haijie Gu, Danny Bickson, Carlos Guestrin:
PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs. OSDI 2012: 17-30 - [c5]Amr Ahmed, Mohamed Aly, Joseph Gonzalez, Shravan M. Narayanamurthy, Alexander J. Smola:
Scalable inference in latent variable models. WSDM 2012: 123-132 - [i4]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
Distributed GraphLab: A Framework for Machine Learning in the Cloud. CoRR abs/1204.6078 (2012) - [i3]Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David R. O'Hallaron:
Distributed Parallel Inference on Large Factor Graphs. CoRR abs/1205.2645 (2012) - 2011
- [c4]Joseph Gonzalez, Yucheng Low, Arthur Gretton, Carlos Guestrin:
Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees. AISTATS 2011: 324-332 - [i2]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin:
GraphLab: A Distributed Framework for Machine Learning in the Cloud. CoRR abs/1107.0922 (2011) - 2010
- [c3]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
GraphLab: A New Framework For Parallel Machine Learning. UAI 2010: 340-349 - [i1]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
GraphLab: A New Framework for Parallel Machine Learning. CoRR abs/1006.4990 (2010)
2000 – 2009
- 2009
- [c2]Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David R. O'Hallaron:
Distributed Parallel Inference on Large Factor Graphs. UAI 2009: 203-212 - [c1]Joseph Gonzalez, Yucheng Low, Carlos Guestrin:
Residual Splash for Optimally Parallelizing Belief Propagation. AISTATS 2009: 177-184
Coauthor Index
Kenneth Y. Goldberg
aka: Ken Goldberg
aka: Ken Goldberg
[c133] [c132] [c131] [c130] [i168] [i166] [i165] [i164] [i162] [i160] [i157] [i156] [j22] [j19] [c121] [c120] [c118] [c116] [c115] [c114] [c113] [c112] [i154] [i153] [i148] [i147] [i146] [i145] [i144] [i139] [i138] [i137] [i134] [c110] [c107] [c105] [c104] [c101] [c97] [i132] [i131] [i125] [i124] [i121] [i119] [i116] [i114] [j16] [c92] [c88] [c87] [c86] [c80] [c79] [c76] [c72] [c69] [c67] [c65] [c63] [c62] [i109] [i104] [i101] [i100] [i94] [i89] [c59] [c57] [c53] [c51] [c49] [c48] [c45] [c42] [i84] [i73] [i69] [i65] [i62] [i54] [i50] [c40] [c33] [c32] [i49] [i48] [i47] [i46] [i44] [i37] [i36] [i35] [c26] [i33] [i29] [i22] [c21] [c20] [i15] [i14] [j3] [i12] [i11] [c12] [i10] [c7]
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last updated on 2024-07-30 20:46 CEST by the dblp team
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