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ORCIDFurong Huang
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- affiliation: University of Maryland, College Park, USA
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2020 – today
- 2024
[j13]Yifan Yang, Mingquan Lin, Han Zhao, Yifan Peng, Furong Huang, Zhiyong Lu:
A survey of recent methods for addressing AI fairness and bias in biomedicine. J. Biomed. Informatics 154: 104646 (2024)- [j12]Furong Huang:
Industrial technology network security measurement in international trade under discrete hopfield neural network. J. Comput. Methods Sci. Eng. 24(2): 657-674 (2024) - [c71]Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Fuxiao Liu, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, Furong Huang:
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. ACL (1) 2024: 416-442 - [c70]Yuhang Zhou, Paiheng Xu, Xiaoyu Liu, Bang An, Wei Ai, Furong Huang:
Explore Spurious Correlations at the Concept Level in Language Models for Text Classification. ACL (1) 2024: 478-492 - [c69]Tianrui Guan, Fuxiao Liu, Xiyang Wu, Ruiqi Xian, Zongxia Li, Xiaoyu Liu, Xijun Wang, Lichang Chen, Furong Huang, Yaser Yacoob, Dinesh Manocha, Tianyi Zhou:
Hallusionbench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models. CVPR 2024: 14375-14385 - [c68]Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang:
PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts. ICLR 2024 - [c67]Souradip Chakraborty, Amrit S. Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha, Mengdi Wang, Furong Huang:
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback. ICLR 2024 - [c66]Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang:
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation. ICLR 2024 - [c65]Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Benjamin Eysenbach, Tuomas Sandholm, Furong Huang, Stephen Marcus McAleer:
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations. ICLR 2024 - [c64]Xiangyu Liu, Souradip Chakraborty, Yanchao Sun, Furong Huang:
Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL. ICLR 2024 - [c63]Xiangyu Liu, Chenghao Deng, Yanchao Sun, Yongyuan Liang, Furong Huang:
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies. ICLR 2024 - [c62]Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Sicheng Zhu, Furong Huang, Tudor Dumitras:
Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds. ICLR 2024 - [c61]Xiyao Wang, Ruijie Zheng, Yanchao Sun, Ruonan Jia, Wichayaporn Wongkamjan, Huazhe Xu, Furong Huang:
COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL. ICLR 2024 - [c60]Guowei Xu, Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Zhecheng Yuan, Tianying Ji, Yu Luo, Xiaoyu Liu, Jiaxin Yuan, Pu Hua, Shuzhen Li, Yanjie Ze, Hal Daumé III, Furong Huang, Huazhe Xu:
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization. ICLR 2024 - [c59]Dehao Yuan, Furong Huang, Cornelia Fermüller, Yiannis Aloimonos:
Decodable and Sample Invariant Continuous Object Encoder. ICLR 2024 - [c58]Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang:
WAVES: Benchmarking the Robustness of Image Watermarks. ICML 2024 - [c57]Souradip Chakraborty, Amrit S. Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang:
Position: On the Possibilities of AI-Generated Text Detection. ICML 2024 - [c56]Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Dinesh Manocha, Furong Huang, Amrit S. Bedi, Mengdi Wang:
MaxMin-RLHF: Alignment with Diverse Human Preferences. ICML 2024 - [c55]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c54]Tianying Ji, Yongyuan Liang, Yan Zeng, Yu Luo, Guowei Xu, Jiawei Guo, Ruijie Zheng, Furong Huang, Fuchun Sun, Huazhe Xu:
ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization. ICML 2024 - [c53]Yuancheng Xu, Chenghao Deng, Yanchao Sun, Ruijie Zheng, Xiyao Wang, Jieyu Zhao, Furong Huang:
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate. ICML 2024 - [c52]Dehao Yuan, Cornelia Fermüller, Tahseen Rabbani, Furong Huang, Yiannis Aloimonos:
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM). ICML 2024 - [c51]Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov:
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control. ICML 2024 - [c50]Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Shuang Ma, Hal Daumé III, Huazhe Xu, John Langford, Praveen Palanisamy, Kalyan Shankar Basu, Furong Huang:
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss. ICML 2024 - [i113]Tahseen Rabbani, Jiahao Su, Xiaoyu Liu, David Chan, Geoffrey Sangston, Furong Huang:
conv_einsum: A Framework for Representation and Fast Evaluation of Multilinear Operations in Convolutional Tensorial Neural Networks. CoRR abs/2401.03384 (2024) - [i112]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i111]Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang:
Benchmarking the Robustness of Image Watermarks. CoRR abs/2401.08573 (2024) - [i110]Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, Furong Huang:
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. CoRR abs/2401.10529 (2024) - [i109]Yifan Yang, Xiaoyu Liu, Qiao Jin, Furong Huang, Zhiyong Lu:
Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation. CoRR abs/2401.13867 (2024) - [i108]Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Shuang Ma, Hal Daumé III, Huazhe Xu, John Langford, Praveen Palanisamy, Kalyan Shankar Basu, Furong Huang:
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss. CoRR abs/2402.06187 (2024) - [i107]Yuancheng Xu, Jiarui Yao, Manli Shu, Yanchao Sun, Zichu Wu, Ning Yu, Tom Goldstein, Furong Huang:
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models. CoRR abs/2402.06659 (2024) - [i106]Yifan Yang, Mingquan Lin, Han Zhao, Yifan Peng, Furong Huang, Zhiyong Lu:
A survey of recent methods for addressing AI fairness and bias in biomedicine. CoRR abs/2402.08250 (2024) - [i105]Souradip Chakraborty, Jiahao Qiu, Hui Yuan, Alec Koppel, Furong Huang, Dinesh Manocha, Amrit Singh Bedi, Mengdi Wang
:
MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences. CoRR abs/2402.08925 (2024) - [i104]Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov:
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem. CoRR abs/2402.10450 (2024) - [i103]Xiangyu Liu, Chenghao Deng, Yanchao Sun, Yongyuan Liang, Furong Huang:
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies. CoRR abs/2402.12673 (2024) - [i102]Tianying Ji, Yongyuan Liang, Yan Zeng, Yu Luo, Guowei Xu, Jiawei Guo, Ruijie Zheng, Furong Huang, Fuchun Sun, Huazhe Xu:
ACE : Off-Policy Actor-Critic with Causality-Aware Entropy Regularization. CoRR abs/2402.14528 (2024) - [i101]Xiaoyu Liu, Paiheng Xu, Junda Wu, Jiaxin Yuan, Yifan Yang, Yuhang Zhou, Fuxiao Liu, Tianrui Guan, Haoliang Wang, Tong Yu, Julian J. McAuley, Wei Ai, Furong Huang:
Large Language Models and Causal Inference in Collaboration: A Comprehensive Survey. CoRR abs/2403.09606 (2024) - [i100]Dehao Yuan, Cornelia Fermüller, Tahseen Rabbani, Furong Huang, Yiannis Aloimonos:
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM). CoRR abs/2404.01568 (2024) - [i99]Marco Bornstein, Amrit Singh Bedi, Abdirisak Mohamed, Furong Huang:
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? CoRR abs/2405.13879 (2024) - [i98]Xiyao Wang, Jiuhai Chen, Zhaoyang Wang, Yuhang Zhou, Yiyang Zhou, Huaxiu Yao, Tianyi Zhou, Tom Goldstein, Parminder Bhatia, Furong Huang, Cao Xiao:
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. CoRR abs/2405.15973 (2024) - [i97]Mucong Ding, Yinhan He, Jundong Li, Furong Huang:
Spectral Greedy Coresets for Graph Neural Networks. CoRR abs/2405.17404 (2024) - [i96]Mucong Ding, Yuancheng Xu, Tahseen Rabbani, Xiaoyu Liu, Brian J. Gravelle, Teresa M. Ranadive, Tai-Ching Tuan, Furong Huang:
Calibrated Dataset Condensation for Faster Hyperparameter Search. CoRR abs/2405.17535 (2024) - [i95]Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang:
Transfer Q Star: Principled Decoding for LLM Alignment. CoRR abs/2405.20495 (2024) - [i94]Zeyuan Liu, Ziyu Huan, Xiyao Wang, Jiafei Lyu, Jian Tao, Xiu Li, Furong Huang, Huazhe Xu:
World Models with Hints of Large Language Models for Goal Achieving. CoRR abs/2406.07381 (2024) - [i93]Xiyang Wu, Tianrui Guan, Dianqi Li, Shuaiyi Huang, Xiaoyu Liu, Xijun Wang, Ruiqi Xian, Abhinav Shrivastava, Furong Huang, Jordan Lee Boyd-Graber, Tianyi Zhou, Dinesh Manocha:
AUTOHALLUSION: Automatic Generation of Hallucination Benchmarks for Vision-Language Models. CoRR abs/2406.10900 (2024) - [i92]Pankayaraj Pathmanathan, Souradip Chakraborty, Xiangyu Liu, Yongyuan Liang, Furong Huang:
Is poisoning a real threat to LLM alignment? Maybe more so than you think. CoRR abs/2406.12091 (2024) - [i91]Yifan Yang, Qiao Jin, Furong Huang, Zhiyong Lu:
Adversarial Attacks on Large Language Models in Medicine. CoRR abs/2406.12259 (2024) - [i90]Yuhang Zhou, Jing Zhu, Paiheng Xu, Xiaoyu Liu, Xiyao Wang, Danai Koutra, Wei Ai, Furong Huang:
Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation. CoRR abs/2406.13114 (2024) - [i89]Mucong Ding, Souradip Chakraborty, Vibhu Agrawal, Zora Che, Alec Koppel, Mengdi Wang, Amrit S. Bedi, Furong Huang:
SAIL: Self-Improving Efficient Online Alignment of Large Language Models. CoRR abs/2406.15567 (2024) - [i88]Mucong Ding, Tahseen Rabbani, Bang An, Evan Z. Wang, Furong Huang:
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. CoRR abs/2406.15575 (2024) - [i87]Yongyuan Liang, Tingqiang Xu, Kaizhe Hu, Guangqi Jiang, Furong Huang, Huazhe Xu:
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion. CoRR abs/2407.10973 (2024) - [i86]Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang:
Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data? CoRR abs/2407.17417 (2024) - [i85]Bang An, Sicheng Zhu, Ruiyi Zhang, Michael-Andrei Panaitescu-Liess, Yuancheng Xu, Furong Huang:
Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models. CoRR abs/2409.00598 (2024) - [i84]Xiaoyu Liu, Jiaxin Yuan, Yuhang Zhou, Jingling Li, Furong Huang, Wei Ai:
CSRec: Rethinking Sequential Recommendation from A Causal Perspective. CoRR abs/2409.05872 (2024) - [i83]Kyle Sang, Tahseen Rabbani, Furong Huang:
Balancing Label Imbalance in Federated Environments Using Only Mixup and Artificially-Labeled Noise. CoRR abs/2409.13235 (2024) - [i82]Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Anima Anandkumar, Furong Huang:
Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. CoRR abs/2409.18433 (2024) - [i81]Marco Bornstein, Zora Che, Suhas Julapalli, Abdirisak Mohamed, Amrit Singh Bedi, Furong Huang:
Auction-Based Regulation for Artificial Intelligence. CoRR abs/2410.01871 (2024) - [i80]Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang:
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation. CoRR abs/2410.02512 (2024) - [i79]Joshua McClellan, Naveed Haghani, John Winder, Furong Huang, Pratap Tokekar:
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance. CoRR abs/2410.02581 (2024) - 2023
- [j11]Haiqiong Yan, Shuang Tang, Furong Huang:
Temporal expectations mediated the repetition effect in a sequence in two ways. Cogn. Process. 24(4): 463-469 (2023) - [j10]Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit S. Bedi:
A Survey on the Possibilities & Impossibilities of AI-generated Text Detection. Trans. Mach. Learn. Res. 2023 (2023) - [c49]Souradip Chakraborty, Amrit Singh Bedi, Pratap Tokekar, Alec Koppel, Brian M. Sadler, Furong Huang, Dinesh Manocha:
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. AAAI 2023: 6980-6988 - [c48]Marco Bornstein, Tahseen Rabbani, Evan Wang, Amrit S. Bedi, Furong Huang:
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication. ICLR 2023 - [c47]Yanchao Sun, Shuang Ma, Ratnesh Madaan, Rogerio Bonatti, Furong Huang, Ashish Kapoor:
SMART: Self-supervised Multi-task pretrAining with contRol Transformers. ICLR 2023 - [c46]Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang:
Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication. ICLR 2023 - [c45]Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang:
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness. ICLR 2023 - [c44]Ruijie Zheng, Xiyao Wang, Huazhe Xu, Furong Huang:
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function. ICLR 2023 - [c43]Souradip Chakraborty, Amrit S. Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha:
STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning. ICML 2023: 3949-3978 - [c42]Xiyao Wang, Wichayaporn Wongkamjan, Ruonan Jia, Furong Huang:
Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy. ICML 2023: 36470-36493 - [c41]Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong:
Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator. ICML 2023: 42915-42937 - [c40]Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. NeurIPS 2023 - [c39]Xiaoyu Liu, Jiaxin Yuan, Bang An, Yuancheng Xu, Yifan Yang, Furong Huang:
C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder. NeurIPS 2023 - [c38]Tahseen Rabbani, Marco Bornstein, Furong Huang:
Large-Scale Distributed Learning via Private On-Device LSH. NeurIPS 2023 - [c37]Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu, Hal Daumé III, Furong Huang:
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning. NeurIPS 2023 - [i78]Yanchao Sun, Shuang Ma, Ratnesh Madaan, Rogerio Bonatti, Furong Huang, Ashish Kapoor:
SMART: Self-supervised Multi-task pretrAining with contRol Transformers. CoRR abs/2301.09816 (2023) - [i77]Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha:
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning. CoRR abs/2301.12038 (2023) - [i76]Ruijie Zheng, Xiyao Wang, Huazhe Xu, Furong Huang:
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function. CoRR abs/2302.01244 (2023) - [i75]Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang:
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness. CoRR abs/2302.03015 (2023) - [i74]Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang:
On the Possibilities of AI-Generated Text Detection. CoRR abs/2304.04736 (2023) - [i73]Paiheng Xu, Yuhang Zhou, Bang An, Wei Ai, Furong Huang:
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint. CoRR abs/2305.15622 (2023) - [i72]Xiangyu Liu, Souradip Chakraborty, Yanchao Sun, Furong Huang:
Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in Multi-Agent RL. CoRR abs/2305.17342 (2023) - [i71]Tahseen Rabbani, Marco Bornstein, Furong Huang:
Large-Scale Distributed Learning via Private On-Device Locality-Sensitive Hashing. CoRR abs/2306.02563 (2023) - [i70]Peijian Ding, Davit Soselia, Thomas Armstrong, Jiahao Su, Furong Huang:
Reviving Shift Equivariance in Vision Transformers. CoRR abs/2306.07470 (2023) - [i69]Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu, Hal Daumé III, Furong Huang:
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning. CoRR abs/2306.13229 (2023) - [i68]Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Tuomas Sandholm, Furong Huang, Stephen McAleer:
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations. CoRR abs/2307.12062 (2023) - [i67]Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang:
More Context, Less Distraction: Visual Classification by Inferring and Conditioning on Contextual Attributes. CoRR abs/2308.01313 (2023) - [i66]Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Dinesh Manocha, Huazheng Wang, Furong Huang, Mengdi Wang:
Aligning Agent Policy with Externalities: Reward Design via Bilevel RL. CoRR abs/2308.02585 (2023) - [i65]Yuancheng Xu, Chenghao Deng, Yanchao Sun, Ruijie Zheng, Xiyao Wang, Jieyu Zhao, Furong Huang:
Equal Long-term Benefit Rate: Adapting Static Fairness Notions to Sequential Decision Making. CoRR abs/2309.03426 (2023) - [i64]Zhili Zhang, Yanchao Sun, Furong Huang, Fei Miao:
Safe and Robust Multi-Agent Reinforcement Learning for Connected Autonomous Vehicles under State Perturbations. CoRR abs/2309.11057 (2023) - [i63]Xiyao Wang, Ruijie Zheng, Yanchao Sun, Ruonan Jia, Wichayaporn Wongkamjan, Huazhe Xu, Furong Huang:
COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL. CoRR abs/2310.07220 (2023) - [i62]Aakriti Agrawal, Rohith Aralikatti, Yanchao Sun, Furong Huang:
Robustness to Multi-Modal Environment Uncertainty in MARL using Curriculum Learning. CoRR abs/2310.08746 (2023) - [i61]Ruijie Zheng, Khanh Nguyen, Hal Daumé III, Furong Huang, Karthik Narasimhan:
Progressively Efficient Learning. CoRR abs/2310.13004 (2023) - [i60]Marco Bornstein, Amrit Singh Bedi, Anit Kumar Sahu, Furqan Khan, Furong Huang:
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation. CoRR abs/2310.13681 (2023) - [i59]Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, Tong Sun:
AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models. CoRR abs/2310.15140 (2023) - [i58]Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit Singh Bedi:
Towards Possibilities & Impossibilities of AI-generated Text Detection: A Survey. CoRR abs/2310.15264 (2023) - [i57]Xiaoyu Liu, Jiaxin Yuan, Bang An, Yuancheng Xu, Yifan Yang, Furong Huang:
C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder. CoRR abs/2310.17325 (2023) - [i56]Guowei Xu, Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Zhecheng Yuan, Tianying Ji, Yu Luo, Xiaoyu Liu, Jiaxin Yuan, Pu Hua, Shuzhen Li, Yanjie Ze, Hal Daumé III, Furong Huang, Huazhe Xu:
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization. CoRR abs/2310.19668 (2023) - [i55]Dehao Yuan, Furong Huang, Cornelia Fermüller, Yiannis Aloimonos:
Decodable and Sample Invariant Continuous Object Encoder. CoRR abs/2311.00187 (2023) - [i54]Yuhang Zhou, Paiheng Xu, Xiaoyu Liu, Bang An, Wei Ai, Furong Huang:
Explore Spurious Correlations at the Concept Level in Language Models for Text Classification. CoRR abs/2311.08648 (2023) - 2022
- [j9]Jiahao Su, Jingling Li, Xiaoyu Liu, Teresa M. Ranadive, Christopher J. Coley, Tai-Ching Tuan, Furong Huang:
Compact Neural Architecture Designs by Tensor Representations. Frontiers Artif. Intell. 5: 728761 (2022) - [j8]Zheng Liang, Songqing Li, Siyuan Zhou, Shi Chen, Ying Li, Yanran Chen, Qingbai Zhao, Furong Huang, Chunming Lu, Quanlei Yu, Zhijin Zhou:
Increased or decreased? Interpersonal neural synchronization in group creation. NeuroImage 260: 119448 (2022) - [c36]Xiaoyu Liu, Jiahao Su, Furong Huang:
Tuformer: Data-driven Design of Transformers for Improved Generalization or Efficiency. ICLR 2022 - [c35]Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang:
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL. ICLR 2022 - [c34]Yanchao Sun, Ruijie Zheng, Xiyao Wang, Andrew E. Cohen, Furong Huang:
Transfer RL across Observation Feature Spaces via Model-Based Regularization. ICLR 2022 - [c33]Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang:
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory. ICLR 2022 - [c32]Jiahao Su, Wonmin Byeon, Furong Huang:
Scaling-up Diverse Orthogonal Convolutional Networks by a Paraunitary Framework. ICML 2022: 20546-20579 - [c31]Bang An, Zora Che, Mucong Ding, Furong Huang:
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization. NeurIPS 2022 - [c30]Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein:
End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking. NeurIPS 2022 - [c29]Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang:
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. NeurIPS 2022 - [c28]Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein:
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability. NeurIPS 2022 - [c27]Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Furong Huang:
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning. NeurIPS 2022 - [c26]Kaiwen Yang, Yanchao Sun, Jiahao Su, Fengxiang He, Xinmei Tian, Furong Huang, Tianyi Zhou, Dacheng Tao:
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach. NeurIPS 2022 - [i53]Yanchao Sun, Ruijie Zheng, Xiyao Wang, Andrew E. Cohen, Furong Huang:
Transfer RL across Observation Feature Spaces via Model-Based Regularization. CoRR abs/2201.00248 (2022) - [i52]Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein:
End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. CoRR abs/2202.05826 (2022) - [i51]Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Brian M. Sadler, Furong Huang, Pratap Tokekar, Dinesh Manocha:
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. CoRR abs/2206.01162 (2022) - [i50]Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang:
Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems. CoRR abs/2206.10158 (2022) - [i49]Amrit Singh Bedi, Chen Fan, Alec Koppel, Anit Kumar Sahu, Brian M. Sadler, Furong Huang, Dinesh Manocha:
FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus. CoRR abs/2206.10815 (2022) - [i48]Bang An, Zora Che, Mucong Ding, Furong Huang:
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization. CoRR abs/2206.12796 (2022) - [i47]Xiyao Wang, Wichayaporn Wongkamjan, Furong Huang:
Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy. CoRR abs/2207.12141 (2022) - [i46]Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein:
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. CoRR abs/2208.09392 (2022) - [i45]Xiaofeng Xue, Haokun Mao, Qiong Li, Furong Huang:
An Energy Optimized Specializing DAG Federated Learning based on Event Triggered Communication. CoRR abs/2209.12531 (2022) - [i44]Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Furong Huang:
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning. CoRR abs/2210.05927 (2022) - [i43]Marco Bornstein, Tahseen Rabbani, Evan Wang, Amrit Singh Bedi, Furong Huang:
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication. CoRR abs/2210.14026 (2022) - [i42]Kaiwen Yang, Yanchao Sun, Jiahao Su, Fengxiang He, Xinmei Tian, Furong Huang, Tianyi Zhou, Dacheng Tao:
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach. CoRR abs/2211.00824 (2022) - [i41]Marco Bornstein, Jin-Peng Liu, Jingling Li, Furong Huang:
Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent. CoRR abs/2211.09908 (2022) - [i40]Paolo Bientinesi, David A. Ham, Furong Huang, Paul H. J. Kelly, P. Sadayappan, Edward Stow:
Tensor Computations: Applications and Optimization (Dagstuhl Seminar 22101). Dagstuhl Reports 12(3): 1-14 (2022) - 2021
- [c25]Yanchao Sun, Xiangyu Yin, Furong Huang:
TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL. AAAI 2021: 9765-9773 - [c24]Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang:
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks. AAAI 2021: 10815-10823 - [c23]Yanchao Sun, Da Huo, Furong Huang:
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics. ICLR 2021 - [c22]Tahseen Rabbani, Apollo Jain, Arjun Rajkumar, Furong Huang:
Practical and Fast Momentum-Based Power Methods. MSML 2021: 721-756 - [c21]Sicheng Zhu, Bang An, Furong Huang:
Understanding the Generalization Benefit of Model Invariance from a Data Perspective. NeurIPS 2021: 4328-4341 - [c20]Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein:
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks. NeurIPS 2021: 6695-6706 - [c19]Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John Dickerson, Furong Huang, Tom Goldstein:
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. NeurIPS 2021: 6733-6746 - [c18]Chen Zhu, Yu Cheng, Zhe Gan, Furong Huang, Jingjing Liu, Tom Goldstein:
MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of Gradients. ECML/PKDD (3) 2021: 628-643 - [i39]Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein:
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. CoRR abs/2103.02079 (2021) - [i38]Hyekang Joo, Calvin Bao, Ishan Sen, Furong Huang, Leilani Battle:
Guided Hyperparameter Tuning Through Visualization and Inference. CoRR abs/2105.11516 (2021) - [i37]Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein:
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks. CoRR abs/2106.04537 (2021) - [i36]Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang:
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL. CoRR abs/2106.05087 (2021) - [i35]Jiahao Su, Wonmin Byeon, Furong Huang:
Scaling-up Diverse Orthogonal Convolutional Networks with a Paraunitary Framework. CoRR abs/2106.09121 (2021) - [i34]Huimin Zeng, Jiahao Su, Furong Huang:
Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders. CoRR abs/2108.00491 (2021) - [i33]Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein:
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability. CoRR abs/2108.01335 (2021) - [i32]Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Arpit Bansal, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein:
Datasets for Studying Generalization from Easy to Hard Examples. CoRR abs/2108.06011 (2021) - [i31]Tahseen Rabbani, Apollo Jain, Arjun Rajkumar, Furong Huang:
Practical and Fast Momentum-Based Power Methods. CoRR abs/2108.09264 (2021) - [i30]Tahseen Rabbani, Brandon Yushan Feng, Yifan Yang, Arjun Rajkumar, Amitabh Varshney, Furong Huang:
Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching. CoRR abs/2109.08346 (2021) - [i29]Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John P. Dickerson, Furong Huang, Tom Goldstein:
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. CoRR abs/2110.14363 (2021) - [i28]Sicheng Zhu, Bang An, Furong Huang:
Understanding the Generalization Benefit of Model Invariance from a Data Perspective. CoRR abs/2111.05529 (2021) - 2020
- [j7]Jingyuan Ren, Furong Huang, Ying Zhou, Liping Zhuang, Jiahua Xu, Chuanji Gao, Shaozheng Qin, Jing Lu:
The function of the hippocampus and middle temporal gyrus in forming new associations and concepts during the processing of novelty and usefulness features in creative designs. NeuroImage 214: 116751 (2020) - [j6]Xuan Wen, Qiong Li, Haokun Mao, Yi Luo, Bing-Ze Yan, Furong Huang:
Novel reconciliation protocol based on spinal code for continuous-variable quantum key distribution. Quantum Inf. Process. 19(9): 350 (2020) - [c17]Jingling Li, Yanchao Sun, Jiahao Su, Taiji Suzuki, Furong Huang:
Understanding Generalization in Deep Learning via Tensor Methods. AISTATS 2020: 504-515 - [c16]Yanchao Sun, Furong Huang:
Can Agents Learn by Analogy?: An Inferable Model for PAC Reinforcement Learning. AAMAS 2020: 1332-1340 - [c15]W. Ronny Huang, Zeyad Emam, Micah Goldblum, Liam Fowl, Justin K. Terry, Furong Huang, Tom Goldstein:
Understanding Generalization Through Visualizations. ICBINB@NeurIPS 2020: 87-97 - [c14]Jiahao Su, Milan Cvitkovic, Furong Huang:
Sampling-Free Learning of Bayesian Quantized Neural Networks. ICLR 2020 - [c13]Chris Decarolis, Mukul Ram, Seyed Esmaeili, Yu-Xiang Wang, Furong Huang:
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm. ICML 2020: 2421-2431 - [c12]Alexander Reustle, Tahseen Rabbani, Furong Huang:
Fast GPU Convolution for CP-Decomposed Tensorial Neural Networks. IntelliSys (1) 2020: 468-487 - [c11]Jiahao Su, Shiqi Wang, Furong Huang:
ARMA Nets: Expanding Receptive Field for Dense Prediction. NeurIPS 2020 - [c10]Jiahao Su, Wonmin Byeon, Jean Kossaifi, Furong Huang, Jan Kautz, Anima Anandkumar:
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning. NeurIPS 2020 - [i27]Jingling Li, Yanchao Sun, Jiahao Su, Taiji Suzuki, Furong Huang:
Understanding Generalization in Deep Learning via Tensor Methods. CoRR abs/2001.05070 (2020) - [i26]Yanchao Sun, Xiangyu Yin, Furong Huang:
TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL. CoRR abs/2002.06659 (2020) - [i25]Jiahao Su, Wonmin Byeon, Furong Huang, Jan Kautz, Animashree Anandkumar:
Convolutional Tensor-Train LSTM for Spatio-temporal Learning. CoRR abs/2002.09131 (2020) - [i24]Chen Zhu, Renkun Ni, Ping-Yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein:
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers. CoRR abs/2002.09766 (2020) - [i23]Jiahao Su, Shiqi Wang, Furong Huang:
ARMA Nets: Expanding Receptive Field for Dense Prediction. CoRR abs/2002.11609 (2020) - [i22]Roozbeh Yousefzadeh, Furong Huang:
Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets. CoRR abs/2006.09879 (2020) - [i21]Chen Zhu, Yu Cheng, Zhe Gan, Furong Huang, Jingjing Liu, Tom Goldstein:
Adaptive Learning Rates with Maximum Variation Averaging. CoRR abs/2006.11918 (2020) - [i20]Yanchao Sun, Furong Huang:
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics. CoRR abs/2009.00774 (2020) - [i19]Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang:
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks. CoRR abs/2010.12989 (2020) - [i18]Paolo Bientinesi, David A. Ham, Furong Huang, Paul H. J. Kelly, Christian Lengauer, Saday Sadayappan:
Tensor Computations: Applications and Optimization (Dagstuhl Seminar 20111). Dagstuhl Reports 10(3): 58-70 (2020)
2010 – 2019
- 2019
- [j5]Furong Huang, Qingbai Zhao, Zhijin Zhou, Jing Luo:
People got lost in solving a set of similar problems. NeuroImage 186: 192-199 (2019) - [c9]Ali Shafahi, Amin Ghiasi, Mahyar Najibi, Furong Huang, John P. Dickerson, Tom Goldstein:
Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing. BMVC 2019: 72 - [c8]Furong Huang, U. N. Niranjan, Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar:
Guaranteed Scalable Learning of Latent Tree Models. UAI 2019: 883-893 - [i17]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) - [i16]W. Ronny Huang, Zeyad Emam, Micah Goldblum, Liam Fowl, Justin K. Terry, Furong Huang, Tom Goldstein:
Understanding Generalization through Visualizations. CoRR abs/1906.03291 (2019) - [i15]Ali Shafahi, Amin Ghiasi, Furong Huang, Tom Goldstein:
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training? CoRR abs/1910.11585 (2019) - [i14]Jiahao Su, Milan Cvitkovic, Furong Huang:
Sampling-Free Learning of Bayesian Quantized Neural Networks. CoRR abs/1912.02992 (2019) - [i13]Yanchao Sun, Furong Huang:
Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning. CoRR abs/1912.10329 (2019) - 2018
- [j4]Furong Huang, Shuang Tang, Pei Sun, Jing Luo:
Neural correlates of novelty and appropriateness processing in externally induced constraint relaxation. NeuroImage 172: 381-389 (2018) - [c7]Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire:
Learning Deep ResNet Blocks Sequentially using Boosting Theory. ICML 2018: 2063-2072 - [i12]Jialin Li, Furong Huang:
Guaranteed Simultaneous Asymmetric Tensor Decomposition via Orthogonalized Alternating Least Squares. CoRR abs/1805.10348 (2018) - [i11]Jiahao Su, Jingling Li, Bobby Bhattacharjee, Furong Huang:
Tensorized Spectrum Preserving Compression for Neural Networks. CoRR abs/1805.10352 (2018) - 2017
- [i10]Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire:
Learning Deep ResNet Blocks Sequentially using Boosting Theory. CoRR abs/1706.04964 (2017) - 2016
- [b1]Furong Huang:
Discovery of Latent Factors in High-dimensional Data Using Tensor Methods. University of California, Irvine, USA, 2016 - [i9]Furong Huang:
Discovery of Latent Factors in High-dimensional Data Using Tensor Methods. CoRR abs/1606.03212 (2016) - [i8]Anthony Gitter, Furong Huang, Ragupathyraj Valluvan, Ernest Fraenkel, Animashree Anandkumar:
Unsupervised learning of transcriptional regulatory networks via latent tree graphical models. CoRR abs/1609.06335 (2016) - [i7]Zheng Xu, Furong Huang, Louiqa Raschid, Tom Goldstein:
Non-negative Factorization of the Occurrence Tensor from Financial Contracts. CoRR abs/1612.03350 (2016) - 2015
- [j3]Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Animashree Anandkumar:
Online tensor methods for learning latent variable models. J. Mach. Learn. Res. 16: 2797-2835 (2015) - [j2]Furong Huang, Jin Fan, Jing Luo:
The neural basis of novelty and appropriateness in processing of creative chunk decomposition. NeuroImage 113: 122-132 (2015) - [c6]Rong Ge, Furong Huang, Chi Jin, Yang Yuan:
Escaping From Saddle Points - Online Stochastic Gradient for Tensor Decomposition. COLT 2015: 797-842 - [c5]Forough Arabshahi, Furong Huang, Animashree Anandkumar, Carter T. Butts, Sean M. Fitzhugh:
Are You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden Group Dynamics via Conditional Latent Tree Models]. ICDM 2015: 697-702 - [c4]Furong Huang, Animashree Anandkumar:
Convolutional Dictionary Learning through Tensor Factorization. FE@NIPS 2015: 116-129 - [i6]Rong Ge, Furong Huang, Chi Jin, Yang Yuan:
Escaping From Saddle Points - Online Stochastic Gradient for Tensor Decomposition. CoRR abs/1503.02101 (2015) - [i5]Furong Huang, Animashree Anandkumar:
Convolutional Dictionary Learning through Tensor Factorization. CoRR abs/1506.03509 (2015) - 2014
- [i4]Furong Huang, U. N. Niranjan, Animashree Anandkumar:
Integrated Structure and Parameters Learning in Latent Tree Graphical Models. CoRR abs/1406.4566 (2014) - [i3]Forough Arabshahi, Furong Huang, Animashree Anandkumar, Carter T. Butts:
Modeling Dynamic Social Interactions via Conditional Latent Tree Models. CoRR abs/1411.1132 (2014) - 2013
- [c3]Furong Huang, Anima Anandkumar:
FCD: Fast-concurrent-distributed load balancing under switching costs and imperfect observations. INFOCOM 2013: 1896-1904 - [i2]Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Prateek Verma, Animashree Anandkumar:
Fast Detection of Overlapping Communities via Online Tensor Methods on GPUs. CoRR abs/1309.0787 (2013) - 2012
- [j1]Animashree Anandkumar, Vincent Y. F. Tan, Furong Huang, Alan S. Willsky:
High-dimensional Gaussian graphical model selection: walk summability and local separation criterion. J. Mach. Learn. Res. 13: 2293-2337 (2012) - [c2]Animashree Anandkumar, Daniel J. Hsu, Furong Huang, Sham M. Kakade:
Learning Mixtures of Tree Graphical Models. NIPS 2012: 1061-1069 - 2011
- [i1]Animashree Anandkumar, Vincent Y. F. Tan, Furong Huang, Alan S. Willsky:
High-Dimensional Structure Estimation in Ising Models: Tractable Graph Families. CoRR abs/1107.1736 (2011) - 2010
- [c1]Furong Huang, Wei Wang, Haiyan Luo, Guanding Yu, Zhaoyang Zhang:
Prediction-Based Spectrum Aggregation with Hardware Limitation in Cognitive Radio Networks. VTC Spring 2010: 1-5
Coauthor Index
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