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ORCIDMengdi Wang
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2025
[j59]Mengdi Wang
, Matthew Cong, Bo Zhu:
An interface tracking method with triangle edge cuts. J. Comput. Phys. 520: 113504 (2025)- 2024
- [j58]Huicheng Hao, Mengdi Wang, Hongyu Wang:
Optimization of Emergency Supply and Distribution of Fresh Agricultural Products Under Public Health Emergencies. IEEE Access 12: 28636-28653 (2024) - [j57]Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel:
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control. J. Mach. Learn. Res. 25: 39:1-39:58 (2024) - [j56]Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. J. Mach. Learn. Res. 25: 226:1-226:67 (2024) - [j55]Min Jiang, Mengdi Wang, Jun Kong:
Prototype equilibrium network with group emotional contagion for few-shot emotion recognition in conversation. Int. J. Mach. Learn. Cybern. 15(6): 2229-2246 (2024) - [j54]Yanyi Chu, Dan Yu, Yupeng Li, Kaixuan Huang, Yue Shen, Le Cong, Jason Zhang, Mengdi Wang:
A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions. Nat. Mac. Intell. 6(4): 449-460 (2024) - [j53]Yanyi Chu, Dan Yu, Yupeng Li, Kaixuan Huang, Yue Shen, Le Cong, Jason Zhang, Mengdi Wang:
Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions. Nat. Mac. Intell. 6(8): 988 (2024) - [j52]Josepha Godivier, Elizabeth A. Lawrence, Mengdi Wang, Chrissy L. Hammond, Niamh C. Nowlan:
Compressive stress gradients direct mechanoregulation of anisotropic growth in the zebrafish jaw joint. PLoS Comput. Biol. 20(2) (2024) - [j51]Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei Zhang:
Boosting the Convergence of Reinforcement Learning-Based Auto-Pruning Using Historical Data. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(2): 548-561 (2024) - [j50]Minshuo Chen, Jie Meng, Yu Bai, Yinyu Ye, H. Vincent Poor, Mengdi Wang:
Efficient Reinforcement Learning With Impaired Observability: Learning to Act With Delayed and Missing State Observations. IEEE Trans. Inf. Theory 70(10): 7251-7272 (2024) - [j49]Liang-Yong Xia, Yu Wu, Longfei Zhao, Leying Chen, Shiyi Zhang, Mengdi Wang, Jie Luo:
Redefining the Game: MVAE-DFDPnet's Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions. IEEE J. Biomed. Health Informatics 28(7): 4317-4324 (2024) - [j48]Zheng Yu, Junyu Zhang, Zheng Wen, Andrea Tacchetti, Mengdi Wang, Ian Gemp:
Teamwork Reinforcement Learning With Concave Utilities. IEEE Trans. Mob. Comput. 23(5): 5709-5721 (2024) - [c115]Jiahao Qiu, Hui Yuan, Jinghong Zhang, Wentao Chen, Huazheng Wang, Mengdi Wang:
Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization. AAAI 2024: 14686-14694 - [c114]Mengdi Wang, Anna Bodonhelyi, Efe Bozkir, Enkelejda Kasneci:
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients. AAAI 2024: 15546-15554 - [c113]Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal:
Visual Adversarial Examples Jailbreak Aligned Large Language Models. AAAI 2024: 21527-21536 - [c112]Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang:
Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis. AISTATS 2024: 2737-2745 - [c111]Fuping Li, Ying Wang, Yujie Wang, Mengdi Wang, Yinhe Han, Huawei Li, Xiaowei Li:
Chipletizer: Repartitioning SoCs for Cost-Effective Chiplet Integration. ASPDAC 2024: 58-64 - [c110]Efe Bozkir, Süleyman Özdel, Ka Hei Carrie Lau, Mengdi Wang, Hong Gao, Enkelejda Kasneci:
Embedding Large Language Models into Extended Reality: Opportunities and Challenges for Inclusion, Engagement, and Privacy. CUI 2024: 38 - [c109]Kaiyan Chang, Kun Wang, Nan Yang, Ying Wang, Dantong Jin, Wenlong Zhu, Zhirong Chen, Cangyuan Li, Hao Yan, Yunhao Zhou, Zhuoliang Zhao, Yuan Cheng, Yudong Pan, Yiqi Liu, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li:
Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework. DAC 2024: 60:1-60:6 - [c108]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 - [c107]Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai:
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight. ICLR 2024 - [c106]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 - [c105]Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang:
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling. ICML 2024 - [c104]Alec Koppel, Sujay Bhatt, Jiacheng Guo, Joe Eappen, Mengdi Wang, Sumitra Ganesh:
Information-Directed Pessimism for Offline Reinforcement Learning. ICML 2024 - [c103]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. ICML 2024 - [c102]Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei:
Theoretical insights for diffusion guidance: A case study for Gaussian mixture models. ICML 2024 - [c101]Lei Zhao, Mengdi Wang, Yu Bai:
Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective. ICML 2024 - [c100]Xifeng Xu, Yunni Xia, Qinglan Peng, Xingli Zhong, Song Zhou, Kai Peng, Mengdi Wang:
A Novel Structured Task Scheduling Approach in Satellite Edge Computing Environments. ICWS 2024: 718-727 - [c99]Shuhua Yang, Hui Yuan, Xiaoying Zhang, Mengdi Wang, Hong Zhang, Huazheng Wang:
Conversational Dueling Bandits in Generalized Linear Models. KDD 2024: 3806-3817 - [i135]Joseph C. Kim, David Bloore, Karan Kapoor, Jun Feng, Ming-Hong Hao, Mengdi Wang:
Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules. CoRR abs/2401.04246 (2024) - [i134]Jiahao Qiu, Hui Yuan, Jinghong Zhang, Wentao Chen, Huazheng Wang, Mengdi Wang:
Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization. CoRR abs/2401.06173 (2024) - [i133]Mengdi Wang, Anna Bodonhelyi, Efe Bozkir, Enkelejda Kasneci:
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients. CoRR abs/2401.12012 (2024) - [i132]Efe Bozkir, Süleyman Özdel, Ka Hei Carrie Lau, Mengdi Wang, Hong Gao, Enkelejda Kasneci:
Embedding Large Language Models into Extended Reality: Opportunities and Challenges for Inclusion, Engagement, and Privacy. CoRR abs/2402.03907 (2024) - [i131]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. CoRR abs/2402.05162 (2024) - [i130]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) - [i129]Zihao Li, Boyi Liu, Zhuoran Yang, Zhaoran Wang, Mengdi Wang:
Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning. CoRR abs/2402.10810 (2024) - [i128]Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei:
Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models. CoRR abs/2403.01639 (2024) - [i127]Zihao Li, Hui Lan, Vasilis Syrgkanis, Mengdi Wang, Masatoshi Uehara:
Regularized DeepIV with Model Selection. CoRR abs/2403.04236 (2024) - [i126]Kaiyan Chang, Kun Wang, Nan Yang, Ying Wang, Dantong Jin, Wenlong Zhu, Zhirong Chen, Cangyuan Li, Hao Yan, Yunhao Zhou, Zhuoliang Zhao, Yuan Cheng, Yudong Pan, Yiqi Liu, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li:
Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework. CoRR abs/2403.11202 (2024) - [i125]Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup:
Offline Multitask Representation Learning for Reinforcement Learning. CoRR abs/2403.11574 (2024) - [i124]Hengyu Fu, Zhuoran Yang, Mengdi Wang, Minshuo Chen:
Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory. CoRR abs/2403.11968 (2024) - [i123]Xudong Guo, Kaixuan Huang, Jiale Liu, Wenhui Fan, Natalia Vélez, Qingyun Wu, Huazheng Wang, Thomas L. Griffiths, Mengdi Wang:
Embodied LLM Agents Learn to Cooperate in Organized Teams. CoRR abs/2403.12482 (2024) - [i122]Zihao Li, Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Yinyu Ye, Minshuo Chen, Mengdi Wang:
Diffusion Model for Data-Driven Black-Box Optimization. CoRR abs/2403.13219 (2024) - [i121]Minshuo Chen, Song Mei, Jianqing Fan, Mengdi Wang:
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization. CoRR abs/2404.07771 (2024) - [i120]Yingqing Guo, Hui Yuan, Yukang Yang, Minshuo Chen, Mengdi Wang:
Gradient Guidance for Diffusion Models: An Optimization Perspective. CoRR abs/2404.14743 (2024) - [i119]Kaixuan Huang, Yuanhao Qu, Henry Cousins, William A. Johnson, Di Yin, Mihir Shah, Denny Zhou, Russ B. Altman, Mengdi Wang, Le Cong:
CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments. CoRR abs/2404.18021 (2024) - [i118]Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal:
AI Risk Management Should Incorporate Both Safety and Security. CoRR abs/2405.19524 (2024) - [i117]Kaixuan Huang, Xudong Guo, Mengdi Wang:
SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths. CoRR abs/2405.19715 (2024) - [i116]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) - [i115]Xiang Ji, Sanjeev Kulkarni, Mengdi Wang, Tengyang Xie:
Self-Play with Adversarial Critic: Provable and Scalable Offline Alignment for Language Models. CoRR abs/2406.04274 (2024) - [i114]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) - [i113]Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang:
Provable Statistical Rates for Consistency Diffusion Models. CoRR abs/2406.16213 (2024) - [i112]Jibang Wu, Siyu Chen, Mengdi Wang, Huazheng Wang, Haifeng Xu:
Contractual Reinforcement Learning: Pulling Arms with Invisible Hands. CoRR abs/2407.01458 (2024) - [i111]Kaiyan Chang, Zhirong Chen, Yunhao Zhou, Wenlong Zhu, Kun Wang, Haobo Xu, Cangyuan Li, Mengdi Wang, Shengwen Liang, Huawei Li, Yinhe Han, Ying Wang:
Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation. CoRR abs/2407.08473 (2024) - [i110]Hengyu Fu, Zehao Dou, Jiawei Guo, Mengdi Wang, Minshuo Chen:
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data. CoRR abs/2407.16134 (2024) - [i109]Shuhua Yang, Hui Yuan, Xiaoying Zhang, Mengdi Wang, Hong Zhang, Huazheng Wang:
Conversational Dueling Bandits in Generalized Linear Models. CoRR abs/2407.18488 (2024) - [i108]Binshuai Wang, Qiwei Di, Ming Yin, Mengdi Wang, Quanquan Gu, Peng Wei:
Relative-Translation Invariant Wasserstein Distance. CoRR abs/2409.02416 (2024) - [i107]Kaixuan Huang, Yukang Yang, Kaidi Fu, Yanyi Chu, Le Cong, Mengdi Wang:
Latent Diffusion Models for Controllable RNA Sequence Generation. CoRR abs/2409.09828 (2024) - [i106]Bhrij Patel, Souradip Chakraborty, Wesley A. Suttle, Mengdi Wang, Amrit Singh Bedi, Dinesh Manocha:
AIME: AI System Optimization via Multiple LLM Evaluators. CoRR abs/2410.03131 (2024) - [i105]Xinchen Zhang, Ling Yang, Guohao Li, Yaqi Cai, Jiake Xie, Yong Tang, Yujiu Yang, Mengdi Wang, Bin Cui:
IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation. CoRR abs/2410.07171 (2024) - [i104]Fu-Yun Wang, Ling Yang, Zhaoyang Huang, Mengdi Wang, Hongsheng Li:
Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow. CoRR abs/2410.07303 (2024) - [i103]Mengdi Wang, Matthew Cong, Bo Zhu:
An Interface Tracking Method with Triangle Edge Cuts. CoRR abs/2410.11073 (2024) - [i102]Lian Liu, Haimeng Ren, Long Cheng, Zhaohui Xu, Yudong Pan, Mengdi Wang, Xiaowei Li, Yinhe Han, Ying Wang:
COMET: Towards Partical W4A4KV4 LLMs Serving. CoRR abs/2410.12168 (2024) - [i101]Hui Yuan, Yifan Zeng, Yue Wu, Huazheng Wang, Mengdi Wang, Liu Leqi:
A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement. CoRR abs/2410.13828 (2024) - [i100]Xun Jiang, Feng Li, Han Zhao, Jiaying Wang, Jun Shao, Shihao Xu, Shu Zhang, Weiling Chen, Xavier Tang, Yize Chen, Mengyue Wu, Weizhi Ma, Mengdi Wang, Tianqiao Chen:
Long Term Memory: The Foundation of AI Self-Evolution. CoRR abs/2410.15665 (2024) - [i99]Jiahao Qiu, Yifu Lu, Yifan Zeng, Jiacheng Guo, Jiayi Geng, Huazheng Wang, Kaixuan Huang, Yue Wu, Mengdi Wang:
TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling. CoRR abs/2410.16033 (2024) - [i98]Hanshi Sun, Momin Haider, Ruiqi Zhang, Huitao Yang, Jiahao Qiu, Ming Yin, Mengdi Wang, Peter L. Bartlett, Andrea Zanette:
Fast Best-of-N Decoding via Speculative Rejection. CoRR abs/2410.20290 (2024) - [i97]Zaixi Zhang, Ruofan Jin, Kaidi Fu, Le Cong, Marinka Zitnik, Mengdi Wang:
FoldMark: Protecting Protein Generative Models with Watermarking. CoRR abs/2410.20354 (2024) - [i96]Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan:
Global Convergence in Training Large-Scale Transformers. CoRR abs/2410.23610 (2024) - [i95]Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang:
A Theoretical Perspective for Speculative Decoding Algorithm. CoRR abs/2411.00841 (2024) - 2023
- [j47]Chengzhuo Ni, Yaqi Duan, Munther A. Dahleh, Mengdi Wang, Anru R. Zhang:
Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition. J. Mach. Learn. Res. 24: 115:1-115:53 (2023) - [j46]Zihao Li, Boyi Liu, Zhuoran Yang, Zhaoran Wang, Mengdi Wang:
Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning. J. Mach. Learn. Res. 24: 385:1-385:43 (2023) - [j45]Mingbao Lin, Yuxin Zhang, Yuchao Li, Bohong Chen, Fei Chao, Mengdi Wang, Shen Li, Yonghong Tian, Rongrong Ji:
1xN Pattern for Pruning Convolutional Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 3999-4008 (2023) - [j44]Junyu Zhang, Mengdi Wang, Mingyi Hong, Shuzhong Zhang:
Primal-Dual First-Order Methods for Affinely Constrained Multi-block Saddle Point Problems. SIAM J. Optim. 33(2): 1035-1060 (2023) - [j43]Mengdi Wang, Di Xiao, Jia Liang, Guiqiang Hu:
Distributed privacy-preserving nested compressed sensing for multiclass data collection with identity authentication. Signal Process. 204: 108823 (2023) - [j42]Mengdi Wang, Hung Chau, Khushboo Thaker, Peter Brusilovsky, Daqing He:
Knowledge Annotation for Intelligent Textbooks. Technol. Knowl. Learn. 28(1): 1-22 (2023) - [c98]Huiqing Xu, Kuang Mao, Quihong Pan, Zhaorong Tang, Mengdi Wang, Ying Wang:
Deep Learning Compiler Optimization on Multi-Chiplet Architecture. AICAS 2023: 1-5 - [c97]Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu:
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. AISTATS 2023: 3230-3269 - [c96]Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang:
Provable Benefits of Representational Transfer in Reinforcement Learning. COLT 2023: 2114-2187 - [c95]Chengsi Gao, Ying Wang, Cheng Liu, Mengdi Wang, Weiwei Chen, Yinhe Han, Lei Zhang:
Layer-Puzzle: Allocating and Scheduling Multi-task on Multi-core NPUs by Using Layer Heterogeneity. DATE 2023: 1-6 - [c94]Hui Huang, Di Xiao, Mengdi Wang:
Hierarchical Privacy-Preserving and Communication-Efficient Compression via Compressed Sensing. DCC 2023: 342 - [c93]Mengdi Wang, You Wu, Tao Ding, Xingwei Zhao, Bo Tao:
The Construction of Intelligent Grasping System Based on EEG. ICIRA (5) 2023: 245-256 - [c92]Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. ICLR 2023 - [c91]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment. ICLR 2023 - [c90]Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Zihan Ding, Chi Jin, Mengdi Wang:
Representation Learning for Low-rank General-sum Markov Games. ICLR 2023 - [c89]Ming Yin, Mengdi Wang, Yu-Xiang Wang:
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. ICLR 2023 - [c88]Zheng Yu, Yikuan Li, Joseph C. Kim, Kaixuan Huang, Yuan Luo, Mengdi Wang:
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis. ICLR 2023 - [c87]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 - [c86]Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang:
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. ICML 2023: 4672-4712 - [c85]Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang:
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP. ICML 2023: 11967-11997 - [c84]Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao:
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. ICML 2023: 40911-40931 - [c83]Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang:
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations. NeurIPS 2023 - [c82]Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma:
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. NeurIPS 2023 - [c81]Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, Mengdi Wang:
Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement. NeurIPS 2023 - [c80]Zeyu Zhang, Yi Su, Hui Yuan, Yiran Wu, Rishab Balasubramanian, Qingyun Wu, Huazheng Wang, Mengdi Wang:
Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective. NeurIPS 2023 - [i94]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) - [i93]Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang:
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. CoRR abs/2302.07194 (2023) - [i92]Zheng Yu, Yikuan Li, Joseph C. Kim, Kaixuan Huang, Yuan Luo, Mengdi Wang:
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis. CoRR abs/2302.10261 (2023) - [i91]Kaiyan Chang, Ying Wang, Haimeng Ren, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li:
ChipGPT: How far are we from natural language hardware design. CoRR abs/2305.14019 (2023) - [i90]Efe Bozkir, Süleyman Özdel, Mengdi Wang, Brendan David-John, Hong Gao, Kevin R. B. Butler, Eakta Jain, Enkelejda Kasneci:
Eye-tracked Virtual Reality: A Comprehensive Survey on Methods and Privacy Challenges. CoRR abs/2305.14080 (2023) - [i89]Zihao Li, Zhuoran Yang, Mengdi Wang:
Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism. CoRR abs/2305.18438 (2023) - [i88]Zichen Wang, Rishab Balasubramanian, Hui Yuan, Chenyu Song, Mengdi Wang, Huazheng Wang:
Adversarial Attacks on Online Learning to Rank with Stochastic Click Models. CoRR abs/2305.19218 (2023) - [i87]Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang:
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations. CoRR abs/2306.01243 (2023) - [i86]Zeyu Zhang, Yi Su, Hui Yuan, Yiran Wu, Rishab Balasubramanian, Qingyun Wu, Huazheng Wang, Mengdi Wang:
Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective. CoRR abs/2306.07528 (2023) - [i85]Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang:
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP. CoRR abs/2306.12356 (2023) - [i84]Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Mengdi Wang, Prateek Mittal:
Visual Adversarial Examples Jailbreak Large Language Models. CoRR abs/2306.13213 (2023) - [i83]Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao:
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. CoRR abs/2306.14859 (2023) - [i82]Kaiqi Zhang, Zixuan Zhang, Minshuo Chen, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang:
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. CoRR abs/2307.01649 (2023) - [i81]Tianle Cai, Kaixuan Huang, Jason D. Lee, Mengdi Wang:
Scaling In-Context Demonstrations with Structured Attention. CoRR abs/2307.02690 (2023) - [i80]Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai:
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight. CoRR abs/2307.02884 (2023) - [i79]Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, Mengdi Wang:
Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement. CoRR abs/2307.07055 (2023) - [i78]Xiang Ji, Huazheng Wang, Minshuo Chen, Tuo Zhao, Mengdi Wang:
Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems. CoRR abs/2307.12975 (2023) - [i77]Siyu Chen, Mengdi Wang, Zhuoran Yang:
Actions Speak What You Want: Provably Sample-Efficient Reinforcement Learning of the Quantal Stackelberg Equilibrium from Strategic Feedbacks. CoRR abs/2307.14085 (2023) - [i76]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) - [i75]Yikuan Li, Chengsheng Mao, Kaixuan Huang, Hanyin Wang, Zheng Yu, Mengdi Wang, Yuan Luo:
Deep Reinforcement Learning for Efficient and Fair Allocation of Health Care Resources. CoRR abs/2309.08560 (2023) - [i74]Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. CoRR abs/2309.13915 (2023) - [i73]Shuoguang Yang, Xuezhou Zhang, Mengdi Wang:
Federated Multi-Level Optimization over Decentralized Networks. CoRR abs/2310.06217 (2023) - [i72]Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang:
Sample Complexity of Preference-Based Nonparametric Off-Policy Evaluation with Deep Networks. CoRR abs/2310.10556 (2023) - [i71]Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yi-An Ma:
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. CoRR abs/2310.18919 (2023) - [i70]Lei Zhao, Mengdi Wang, Yu Bai:
Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? CoRR abs/2312.00054 (2023) - 2022
- [j41]Ziwei Zhu, Xudong Li, Mengdi Wang, Anru Zhang:
Learning Markov Models Via Low-Rank Optimization. Oper. Res. 70(4): 2384-2398 (2022) - [j40]Xifeng Xu, Yunni Xia, Feng Zeng, Fan Li, Hong Xie, Xiaodong Fu, Mengdi Wang:
A novel vehicular task deployment method in hybrid MEC. J. Cloud Comput. 11: 88 (2022) - [j39]Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui:
Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality. Patterns 3(12): 100640 (2022) - [j38]Qitong Xu, Chang Liu, Enshan Yang, Mengdi Wang:
An Improved Convolutional Capsule Network for Compound Fault Diagnosis of RV Reducers. Sensors 22(17): 6442 (2022) - [j37]Zhijian Zhou, Yihang Wang, Weijie Sun, Mengdi Wang:
Weight Optimization of the Induction Magnetometer at Low Frequency. IEEE Trans. Instrum. Meas. 71: 1-6 (2022) - [j36]Shiying Xiong, Zhecheng Wang, Mengdi Wang, Bo Zhu:
A clebsch method for free-surface vortical flow simulation. ACM Trans. Graph. 41(4): 116:1-116:13 (2022) - [j35]Yitong Deng, Mengdi Wang, Xiangxin Kong, Shiying Xiong, Zangyueyang Xian, Bo Zhu:
A moving eulerian-lagrangian particle method for thin film and foam simulation. ACM Trans. Graph. 41(4): 154:1-154:17 (2022) - [j34]Jinyuan Liu, Mengdi Wang, Fan Feng, Annie Tang, Qiqin Le, Bo Zhu:
Hydrophobic and Hydrophilic Solid-Fluid Interaction. ACM Trans. Graph. 41(6): 256:1-256:15 (2022) - [c79]Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel:
Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic. AAAI 2022: 9031-9039 - [c78]Chenyu Wang, Joseph C. Kim, Le Cong, Mengdi Wang:
Neural Bandits for Protein Sequence Optimization. CISS 2022: 188-193 - [c77]Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang:
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. ICLR 2022 - [c76]Chengzhuo Ni, Ruiqi Zhang, Xiang Ji, Xuezhou Zhang, Mengdi Wang:
Optimal Estimation of Policy Gradient via Double Fitted Iteration. ICML 2022: 16724-16783 - [c75]Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun:
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach. ICML 2022: 26517-26547 - [c74]Ruiqi Zhang, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang:
Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory. ICML 2022: 26713-26749 - [c73]Yuchao Li, Fuli Luo, Chuanqi Tan, Mengdi Wang, Songfang Huang, Shen Li, Junjie Bai:
Parameter-Efficient Sparsity for Large Language Models Fine-Tuning. IJCAI 2022: 4223-4229 - [c72]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Communication Efficient Distributed Learning for Kernelized Contextual Bandits. NeurIPS 2022 - [c71]Shuoguang Yang, Xuezhou Zhang, Mengdi Wang:
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks. NeurIPS 2022 - [c70]Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvári, Mengdi Wang:
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization. NeurIPS 2022 - [c69]Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang:
Offline stochastic shortest path: Learning, evaluation and towards optimality. UAI 2022: 2278-2288 - [i69]Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun:
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach. CoRR abs/2202.00063 (2022) - [i68]Chengzhuo Ni, Ruiqi Zhang, Xiang Ji, Xuezhou Zhang, Mengdi Wang:
Optimal Estimation of Off-Policy Policy Gradient via Double Fitted Iteration. CoRR abs/2202.00076 (2022) - [i67]Ruiqi Zhang, Xuezhou Zhang, Chengzhuo Ni, Mengdi Wang:
Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory. CoRR abs/2202.04970 (2022) - [i66]Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang:
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. CoRR abs/2203.05804 (2022) - [i65]Yuchao Li, Fuli Luo, Chuanqi Tan, Mengdi Wang, Songfang Huang, Shen Li, Junjie Bai:
Parameter-Efficient Sparsity for Large Language Models Fine-Tuning. CoRR abs/2205.11005 (2022) - [i64]Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang:
Provable Benefits of Representational Transfer in Reinforcement Learning. CoRR abs/2205.14571 (2022) - [i63]Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu:
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. CoRR abs/2206.00165 (2022) - [i62]Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvári, Mengdi Wang:
Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization. CoRR abs/2206.02092 (2022) - [i61]Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. CoRR abs/2206.02887 (2022) - [i60]Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang:
Communication Efficient Distributed Learning for Kernelized Contextual Bandits. CoRR abs/2206.04835 (2022) - [i59]Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang:
Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality. CoRR abs/2206.04921 (2022) - [i58]Shuoguang Yang, Xuezhou Zhang, Mengdi Wang:
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks. CoRR abs/2206.10870 (2022) - [i57]Kaixuan Huang, Yu Wu, Xuezhou Zhang, Shenyinying Tu, Qingyun Wu, Mengdi Wang, Huazheng Wang:
Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization. CoRR abs/2206.14846 (2022) - [i56]Ming Yin, Mengdi Wang, Yu-Xiang Wang:
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. CoRR abs/2210.00750 (2022) - [i55]Chengzhuo Ni, Yuda Song, Xuezhou Zhang, Chi Jin, Mengdi Wang:
Representation Learning for General-sum Low-rank Markov Games. CoRR abs/2210.16976 (2022) - [i54]Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui:
Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality. CoRR abs/2211.04584 (2022) - [i53]Jinghan Wang, Mengdi Wang, Lin F. Yang:
Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP. CoRR abs/2212.00603 (2022) - 2021
- [j33]Shou-Guang Yao, Yunfei Wang, Mengdi Wang, Xiaoyu Shen:
Sneak Analysis Based on Energy Flow in Thermal Systems With Recirculation Structure. IEEE Access 9: 154815-154826 (2021) - [j32]Mengdi Wang, Di Xiao, Yong Xiang:
Low-Cost and Confidentiality-Preserving Multi-Image Compressed Acquisition and Separate Reconstruction for Internet of Multimedia Things. IEEE Internet Things J. 8(3): 1662-1673 (2021) - [j31]Yue Xu, Zengde Deng, Mengdi Wang, Wenjun Xu, Anthony Man-Cho So, Shuguang Cui:
Voting-Based Multiagent Reinforcement Learning for Intelligent IoT. IEEE Internet Things J. 8(4): 2681-2693 (2021) - [j30]Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel:
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. IEEE J. Sel. Areas Inf. Theory 2(2): 611-626 (2021) - [j29]Mengdi Wang, Yitong Deng, Xiangxin Kong, Aditya H. Prasad, Shiying Xiong, Bo Zhu:
Thin-film smoothed particle hydrodynamics fluid. ACM Trans. Graph. 40(4): 110:1-110:16 (2021) - [c68]Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Online Sparse Reinforcement Learning. AISTATS 2021: 316-324 - [c67]Junyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang:
Generalization Bounds for Stochastic Saddle Point Problems. AISTATS 2021: 568-576 - [c66]Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel:
Beyond Cumulative Returns via Reinforcement Learning over State-Action Occupancy Measures. ACC 2021: 894-901 - [c65]Amrit Singh Bedi, Alec Koppel, Mengdi Wang, Junyu Zhang:
Intermittent Communications in Decentralized Shadow Reward Actor-Critic. CDC 2021: 2613-2620 - [c64]Yuchao Li, Shaohui Lin, Jianzhuang Liu, Qixiang Ye, Mengdi Wang, Fei Chao, Fan Yang, Jincheng Ma, Qi Tian, Rongrong Ji:
Towards Compact CNNs via Collaborative Compression. CVPR 2021: 6438-6447 - [c63]Mengdi Wang, Ying Wang, Cheng Liu, Lei Zhang:
Network-on-Interposer Design for Agile Neural-Network Processor Chip Customization. DAC 2021: 49-54 - [c62]Bo Zhang, Di Xiao, Mengdi Wang, Jia Liang:
Privacy-Preserving Compressed Sensing for Image Simultaneous Compression-Encryption Applications. DCC 2021: 283-292 - [c61]Woon Sang Cho, Yizhe Zhang, Sudha Rao, Asli Celikyilmaz, Chenyan Xiong, Jianfeng Gao, Mengdi Wang, Bill Dolan:
Contrastive Multi-document Question Generation. EACL 2021: 12-30 - [c60]Mengdi Wang, Bing Li, Ying Wang, Cheng Liu, Xiaohan Ma, Xiandong Zhao, Lei Zhang:
MT-DLA: An Efficient Multi-Task Deep Learning Accelerator Design. ACM Great Lakes Symposium on VLSI 2021: 1-8 - [c59]Mengdi Wang, Di Xiao, Jia Liang:
Low Complexity Secure P-Tensor Product Compressed Sensing Reconstruction Outsourcing and Identity Authentication in Cloud. ICASSP 2021: 2630-2634 - [c58]Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. ICML 2021: 4063-4073 - [c57]Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang:
Bootstrapping Fitted Q-Evaluation for Off-Policy Inference. ICML 2021: 4074-4084 - [c56]Chengzhuo Ni, Anru R. Zhang, Yaqi Duan, Mengdi Wang:
Learning Good State and Action Representations via Tensor Decomposition. ISIT 2021: 1682-1687 - [c55]Junyu Zhang, Chengzhuo Ni, Zheng Yu, Csaba Szepesvári, Mengdi Wang:
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method. NeurIPS 2021: 2228-2240 - [i52]Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang:
Bootstrapping Statistical Inference for Off-Policy Evaluation. CoRR abs/2102.03607 (2021) - [i51]Junyu Zhang, Chengzhuo Ni, Zheng Yu, Csaba Szepesvári, Mengdi Wang:
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method. CoRR abs/2102.08607 (2021) - [i50]Chengzhuo Ni, Anru Zhang, Yaqi Duan, Mengdi Wang:
Learning Good State and Action Representations via Tensor Decomposition. CoRR abs/2105.01136 (2021) - [i49]Mengdi Wang, Yitong Deng, Xiangxin Kong, Aditya H. Prasad, Shiying Xiong, Bo Zhu:
Thin-Film Smoothed Particle Hydrodynamics Fluid. CoRR abs/2105.07656 (2021) - [i48]Yuchao Li, Shaohui Lin, Jianzhuang Liu, Qixiang Ye, Mengdi Wang, Fei Chao, Fan Yang, Jincheng Ma, Qi Tian, Rongrong Ji:
Towards Compact CNNs via Collaborative Compression. CoRR abs/2105.11228 (2021) - [i47]Mingbao Lin, Yuchao Li, Yuxin Zhang, Bohong Chen, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji:
1×N Block Pattern for Network Sparsity. CoRR abs/2105.14713 (2021) - [i46]Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel:
MARL with General Utilities via Decentralized Shadow Reward Actor-Critic. CoRR abs/2106.00543 (2021) - [i45]Shaokun Zhang, Xiawu Zheng, Chenyi Yang, Yuchao Li, Yan Wang, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji:
You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient. CoRR abs/2106.02435 (2021) - [i44]Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel:
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control. CoRR abs/2106.08414 (2021) - [i43]Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei Zhang:
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data. CoRR abs/2107.08815 (2021) - [i42]Yaqi Duan, Mengdi Wang, Martin J. Wainwright:
Optimal policy evaluation using kernel-based temporal difference methods. CoRR abs/2109.12002 (2021) - 2020
- [j28]Di Xiao, Min Li, Mengdi Wang, Jia Liang, Ran Liu:
Low-cost and high-efficiency privacy-protection scheme for distributed compressive video sensing in wireless multimedia sensor networks. J. Netw. Comput. Appl. 161: 102654 (2020) - [j27]Mengdi Wang:
Randomized Linear Programming Solves the Markov Decision Problem in Nearly Linear (Sometimes Sublinear) Time. Math. Oper. Res. 45(2): 517-546 (2020) - [j26]Saeed Ghadimi, Andrzej Ruszczynski, Mengdi Wang:
A Single Timescale Stochastic Approximation Method for Nested Stochastic Optimization. SIAM J. Optim. 30(1): 960-979 (2020) - [j25]Yaqi Duan, Mengdi Wang, Zaiwen Wen, Yaxiang Yuan:
Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains. SIAM J. Matrix Anal. Appl. 41(1): 244-278 (2020) - [j24]Di Xiao, Fei Li, Mengdi Wang, Hongying Zheng:
A Novel High-Capacity Data Hiding in Encrypted Images Based on Compressive Sensing Progressive Recovery. IEEE Signal Process. Lett. 27: 296-300 (2020) - [j23]Anru Zhang, Mengdi Wang:
Spectral State Compression of Markov Processes. IEEE Trans. Inf. Theory 66(5): 3202-3231 (2020) - [c54]Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang:
Sketching Transformed Matrices with Applications to Natural Language Processing. AISTATS 2020: 467-481 - [c53]Aaron Sidford, Mengdi Wang, Lin Yang, Yinyu Ye:
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity. AISTATS 2020: 2992-3002 - [c52]Tianyi Lin, Chengyou Fan, Mengdi Wang, Michael I. Jordan:
Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient. ACC 2020: 126-131 - [c51]Jiandong Mu, Mengdi Wang, Lanbo Li, Jun Yang, Wei Lin, Wei Zhang:
A History-Based Auto-Tuning Framework for Fast and High-Performance DNN Design on GPU. DAC 2020: 1-6 - [c50]Ying Wang, Mengdi Wang, Bing Li, Huawei Li, Xiaowei Li:
A Many-Core Accelerator Design for On-Chip Deep Reinforcement Learning. ICCAD 2020: 46:1-46:7 - [c49]Alex Ayoub, Zeyu Jia, Csaba Szepesvári, Mengdi Wang, Lin Yang:
Model-Based Reinforcement Learning with Value-Targeted Regression. ICML 2020: 463-474 - [c48]Yaqi Duan, Zeyu Jia, Mengdi Wang:
Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation. ICML 2020: 2701-2709 - [c47]Lin Yang, Mengdi Wang:
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound. ICML 2020: 10746-10756 - [c46]Zeyu Jia, Lin Yang, Csaba Szepesvári, Mengdi Wang:
Model-Based Reinforcement Learning with Value-Targeted Regression. L4DC 2020: 666-686 - [c45]Hao Gong, Mengdi Wang:
A Duality Approach for Regret Minimization in Average-Award Ergodic Markov Decision Processes. L4DC 2020: 862-883 - [c44]Xiaodong Yi, Ziyue Luo, Chen Meng, Mengdi Wang, Guoping Long, Chuan Wu, Jun Yang, Wei Lin:
Fast Training of Deep Learning Models over Multiple GPUs. Middleware 2020: 105-118 - [c43]Botao Hao, Tor Lattimore, Mengdi Wang:
High-Dimensional Sparse Linear Bandits. NeurIPS 2020 - [c42]Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu:
Generalized Leverage Score Sampling for Neural Networks. NeurIPS 2020 - [c41]Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan:
Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations. NeurIPS 2020 - [c40]Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang:
Variational Policy Gradient Method for Reinforcement Learning with General Utilities. NeurIPS 2020 - [i41]Yaqi Duan, Mengdi Wang:
Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation. CoRR abs/2002.09516 (2020) - [i40]Yingyu Liang, Zhao Song, Mengdi Wang, Lin F. Yang, Xin Yang:
Sketching Transformed Matrices with Applications to Natural Language Processing. CoRR abs/2002.09812 (2020) - [i39]Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel:
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. CoRR abs/2002.12475 (2020) - [i38]Mengdi Wang, Hung Chau, Khushboo Thaker, Peter Brusilovsky, Daqing He:
Concept Annotation for Intelligent Textbooks. CoRR abs/2005.11422 (2020) - [i37]Alex Ayoub, Zeyu Jia, Csaba Szepesvári, Mengdi Wang, Lin F. Yang:
Model-Based Reinforcement Learning with Value-Targeted Regression. CoRR abs/2006.01107 (2020) - [i36]Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao:
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. CoRR abs/2006.15261 (2020) - [i35]Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang:
Variational Policy Gradient Method for Reinforcement Learning with General Utilities. CoRR abs/2007.02151 (2020) - [i34]Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu:
Generalized Leverage Score Sampling for Neural Networks. CoRR abs/2009.09829 (2020) - [i33]Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Online Sparse Reinforcement Learning. CoRR abs/2011.04018 (2020) - [i32]Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang:
Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient. CoRR abs/2011.04019 (2020) - [i31]Botao Hao, Tor Lattimore, Mengdi Wang:
High-Dimensional Sparse Linear Bandits. CoRR abs/2011.04020 (2020) - [i30]Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan:
Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations. CoRR abs/2011.04622 (2020)
2010 – 2019
- 2019
- [j22]Mengdi Wang, Di Xiao, Yanping Xiang, Hui Wang:
Privacy-Aware Controllable Compressed Data Publishing Against Sparse Estimation Attack in IoT. IEEE Internet Things J. 6(4): 7305-7318 (2019) - [j21]Yichen Chen, Yinyu Ye, Mengdi Wang:
Approximation Hardness for A Class of Sparse Optimization Problems. J. Mach. Learn. Res. 20: 38:1-38:27 (2019) - [j20]Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao:
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. J. Mach. Learn. Res. 20: 44:1-44:5 (2019) - [j19]Ethan X. Fang, Han Liu, Mengdi Wang:
Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach. Math. Program. 176(1-2): 175-205 (2019) - [j18]Shuoguang Yang, Mengdi Wang, Ethan X. Fang:
Multilevel Stochastic Gradient Methods for Nested Composition Optimization. SIAM J. Optim. 29(1): 616-659 (2019) - [c39]Chengzhuo Ni, Lin F. Yang, Mengdi Wang:
Learning to Control in Metric Space with Optimal Regret. Allerton 2019: 726-733 - [c38]Mengdi Wang, Di Xiao, Zihang Ao:
A Novel Privacy-Preserving Data Gathering Scheme in WSN Based on Compressive Sensing and Embedding. ICC 2019: 1-6 - [c37]Lin Yang, Mengdi Wang:
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features. ICML 2019: 6995-7004 - [c36]Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu, Jun Yang, Wei Lin, Yangqing Jia:
Characterizing Deep Learning Training Workloads on Alibaba-PAI. IISWC 2019: 189-202 - [c35]Chengzhuo Ni, Mengdi Wang:
Maximum Likelihood Tensor Decomposition of Markov Decision Process. ISIT 2019: 3062-3066 - [c34]Di Jin, Mark Heimann, Tara Safavi, Mengdi Wang, Wei Lee, Lindsay Snider, Danai Koutra:
Smart Roles: Inferring Professional Roles in Email Networks. KDD 2019: 2923-2933 - [c33]Yaqi Duan, Zheng Tracy Ke, Mengdi Wang:
State Aggregation Learning from Markov Transition Data. NeurIPS 2019: 4488-4497 - [c32]Yifan Sun, Yaqi Duan, Hao Gong, Mengdi Wang:
Learning low-dimensional state embeddings and metastable clusters from time series data. NeurIPS 2019: 4563-4572 - [c31]Lin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang:
Online Factorization and Partition of Complex Networks by Random Walk. UAI 2019: 820-830 - [i29]Lin F. Yang, Mengdi Wang:
Sample-Optimal Parametric Q-Learning with Linear Transition Models. CoRR abs/1902.04779 (2019) - [i28]Lin F. Yang, Chengzhuo Ni, Mengdi Wang:
Learning to Control in Metric Space with Optimal Regret. CoRR abs/1905.01576 (2019) - [i27]Lin F. Yang, Mengdi Wang:
Reinforcement Leaning in Feature Space: Matrix Bandit, Kernels, and Regret Bound. CoRR abs/1905.10389 (2019) - [i26]Yifan Sun, Yaqi Duan, Hao Gong, Mengdi Wang:
Learning low-dimensional state embeddings and metastable clusters from time series data. CoRR abs/1906.00302 (2019) - [i25]Zeyu Jia, Lin F. Yang, Mengdi Wang:
Feature-Based Q-Learning for Two-Player Stochastic Games. CoRR abs/1906.00423 (2019) - [i24]Hao Lu, Mengdi Wang:
RL4health: Crowdsourcing Reinforcement Learning for Knee Replacement Pathway Optimization. CoRR abs/1906.01407 (2019) - [i23]Yue Xu, Zengde Deng, Mengdi Wang, Wenjun Xu, Anthony Man-Cho So, Shuguang Cui:
Voting-Based Multi-Agent Reinforcement Learning. CoRR abs/1907.01385 (2019) - [i22]Aaron Sidford, Mengdi Wang, Lin F. Yang, Yinyu Ye:
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity. CoRR abs/1908.11071 (2019) - [i21]Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu, Jun Yang, Wei Lin, Yangqing Jia:
Characterizing Deep Learning Training Workloads on Alibaba-PAI. CoRR abs/1910.05930 (2019) - [i20]Simon S. Du, Ruosong Wang, Mengdi Wang, Lin F. Yang:
Continuous Control with Contexts, Provably. CoRR abs/1910.13614 (2019) - [i19]Woon Sang Cho, Yizhe Zhang, Sudha Rao, Asli Celikyilmaz, Chenyan Xiong, Jianfeng Gao, Mengdi Wang, Bill Dolan:
Unsupervised Common Question Generation from Multiple Documents using Reinforced Contrastive Coordinator. CoRR abs/1911.03047 (2019) - 2018
- [j17]Youmei Zhang, Faliang Chang, Mengdi Wang, Fulei Zhang, Chao Han:
Auxiliary learning for crowd counting via count-net. Neurocomputing 273: 190-198 (2018) - [j16]Mengdi Wang, Faliang Chang, Youmei Zhang:
Crowd escape event detection based on Direction-Collectiveness Model. KSII Trans. Internet Inf. Syst. 12(9): 4355-4374 (2018) - [j15]Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang:
Near-optimal stochastic approximation for online principal component estimation. Math. Program. 167(1): 75-97 (2018) - [j14]Di Xiao, Juan Zhao, Mengdi Wang, Yong Wang:
Controllable high-capacity separable data hiding in encrypted images by compressive sensing and data pretreatment. Multim. Tools Appl. 77(18): 23949-23968 (2018) - [c30]Jason Ge, Zhaoran Wang, Mengdi Wang, Han Liu:
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems. AISTATS 2018: 1589-1598 - [c29]Qing Zhang, Mengru Zhang, Mengdi Wang, Wanchen Sui, Chen Meng, Jun Yang, Weidan Kong, Xiaoyuan Cui, Wei Lin:
Efficient Deep Learning Inference Based on Model Compression. CVPR Workshops 2018: 1695-1702 - [c28]Mengdi Wang, Kun Zhang:
A Practice to Search the Summit of a DEM Using Simulated Annealing Technique. Geoinformatics 2018: 1-5 - [c27]Yichen Chen, Lihong Li, Mengdi Wang:
Scalable Bilinear Learning Using State and Action Features. ICML 2018: 833-842 - [c26]Xudong Li, Mengdi Wang, Anru Zhang:
Estimation of Markov Chain via Rank-constrained Likelihood. ICML 2018: 3039-3048 - [c25]Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao:
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. NeurIPS 2018: 3500-3510 - [c24]Aaron Sidford, Mengdi Wang, Xian Wu, Lin Yang, Yinyu Ye:
Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model. NeurIPS 2018: 5192-5202 - [c23]Aaron Sidford, Mengdi Wang, Xian Wu, Yinyu Ye:
Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes. SODA 2018: 770-787 - [i18]Anru Zhang, Mengdi Wang:
State Compression of Markov Processes via Empirical Low-Rank Estimation. CoRR abs/1802.02920 (2018) - [i17]Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao:
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. CoRR abs/1803.02312 (2018) - [i16]Xudong Li, Mengdi Wang, Anru Zhang:
Estimation of Markov Chain via Rank-constrained Likelihood. CoRR abs/1804.00795 (2018) - [i15]Yichen Chen, Lihong Li, Mengdi Wang:
Scalable Bilinear π Learning Using State and Action Features. CoRR abs/1804.10328 (2018) - [i14]Tianyi Lin, Chenyou Fan, Mengdi Wang, Michael I. Jordan:
Improved Oracle Complexity for Stochastic Compositional Variance Reduced Gradient. CoRR abs/1806.00458 (2018) - [i13]Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang:
Diffusion Approximations for Online Principal Component Estimation and Global Convergence. CoRR abs/1808.09645 (2018) - [i12]Woon Sang Cho, Pengchuan Zhang, Yizhe Zhang, Xiujun Li, Michel Galley, Mengdi Wang, Jianfeng Gao:
A bird's-eye view on coherence, and a worm's-eye view on cohesion. CoRR abs/1811.00511 (2018) - [i11]Yaqi Duan, Zheng Tracy Ke, Mengdi Wang:
State Aggregation Learning from Markov Transition Data. CoRR abs/1811.02619 (2018) - [i10]Mengdi Wang, Qing Zhang, Jun Yang, Xiaoyuan Cui, Wei Lin:
Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks. CoRR abs/1811.08589 (2018) - 2017
- [j13]Mengdi Wang, Anrong Xue, Huanhuan Xia:
Abnormal Event Detection in Wireless Sensor Networks Based on Multiattribute Correlation. J. Electr. Comput. Eng. 2017: 2587948:1-2587948:8 (2017) - [j12]Mengdi Wang, Ji Liu, Ethan X. Fang:
Accelerating Stochastic Composition Optimization. J. Mach. Learn. Res. 18: 105:1-105:23 (2017) - [j11]Mengdi Wang, Youmei Zhang, Faliang Chang:
基于边缘检测和特征融合的自然场景文本定位 (Text Localization Based on Edge Detection and Features Fusion in Natural Scene). 计算机科学 44(9): 300-303 (2017) - [j10]Mengdi Wang, Jing Yu, Lijuan Niu, Weidong Sun:
Feature Extraction for Hyperspectral Images Using Low-Rank Representation With Neighborhood Preserving Regularization. IEEE Geosci. Remote. Sens. Lett. 14(6): 836-840 (2017) - [j9]Mengdi Wang, Ethan X. Fang, Han Liu:
Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions. Math. Program. 161(1-2): 419-449 (2017) - [j8]Mengdi Wang:
Vanishing Price of Decentralization in Large Coordinative Nonconvex Optimization. SIAM J. Optim. 27(3): 1977-2009 (2017) - [c22]Xiangru Lian, Mengdi Wang, Ji Liu:
Finite-sum Composition Optimization via Variance Reduced Gradient Descent. AISTATS 2017: 1159-1167 - [c21]Mengdi Wang, Jing Yu, Lijuan Niu, Weidong Sun:
Unsupervised feature extraction for hyperspectral images using combined low rank representation and locally linear embedding. ICASSP 2017: 1428-1431 - [c20]Mengdi Wang, Jing Yu, Weidong Sun:
LRR-based hyperspectral image restoration by exploiting the union structure of spectral space and with robust dictionary estimation. ICIP 2017: 4287-4291 - [c19]Yichen Chen, Dongdong Ge, Mengdi Wang, Zizhuo Wang, Yinyu Ye, Hao Yin:
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions. ICML 2017: 740-747 - [c18]Chris Junchi Li, Mengdi Wang, Tong Zhang:
Diffusion Approximations for Online Principal Component Estimation and Global Convergence. NIPS 2017: 645-655 - [c17]Fanpeng Meng, Yijun Gu, Shunshun Fu, Mengdi Wang, Yuchen Guo:
Comparison of Different Centrality Measures to Find Influential Nodes in Complex Networks. SpaCCS Workshops 2017: 415-423 - [c16]Xingsheng He, Di Lu, Drew Margolin, Mengdi Wang, Salma El Idrissi, Yu-Ru Lin:
The Signals and Noise: Actionable Information in Improvised Social Media Channels During a Disaster. WebSci 2017: 33-42 - [i9]Mengdi Wang:
Randomized Linear Programming Solves the Discounted Markov Decision Problem In Nearly-Linear Running Time. CoRR abs/1704.01869 (2017) - [i8]Yichen Chen, Mengdi Wang:
Lower Bound On the Computational Complexity of Discounted Markov Decision Problems. CoRR abs/1705.07312 (2017) - [i7]Lin F. Yang, Vladimir Braverman, Tuo Zhao, Mengdi Wang:
Dynamic Factorization and Partition of Complex Networks. CoRR abs/1705.07881 (2017) - [i6]Mengdi Wang:
Primal-Dual π Learning: Sample Complexity and Sublinear Run Time for Ergodic Markov Decision Problems. CoRR abs/1710.06100 (2017) - [i5]Aaron Sidford, Mengdi Wang, Xian Wu, Yinyu Ye:
Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes. CoRR abs/1710.09988 (2017) - [i4]Woon Sang Cho, Mengdi Wang:
Deep Primal-Dual Reinforcement Learning: Accelerating Actor-Critic using Bellman Duality. CoRR abs/1712.02467 (2017) - 2016
- [j7]Anrong Xue, Wenyuan Mao, Mengdi Wang, Quanzhen Chen:
基于贝叶斯方法和变化表的恐怖行为预测算法 (Terrorism Prediction Based on Bayes Method and Change Table). 计算机科学 43(12): 130-134 (2016) - [j6]Mengdi Wang, Dimitri P. Bertsekas:
Stochastic First-Order Methods with Random Constraint Projection. SIAM J. Optim. 26(1): 681-717 (2016) - [j5]Mengdi Wang, Jing Yu, Jing-Hao Xue, Weidong Sun:
Denoising of Hyperspectral Images Using Group Low-Rank Representation. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 9(9): 4420-4427 (2016) - [j4]Qian Fu, Zhongke Wu, Xiang Ying, Mengdi Wang, Xia Zheng, Mingquan Zhou:
Generating Chinese Calligraphy on Freeform Shapes. Trans. Comput. Sci. 28: 69-87 (2016) - [c15]Mengdi Wang, Yichen Chen:
An online primal-dual method for discounted Markov decision processes. CDC 2016: 4516-4521 - [c14]Mengdi Wang, Jing Yu, Lijuan Niu, Weidong Sun:
Hyperspectral Image Denoising Based on Subspace Low Rank Representation. GRMSE (2) 2016: 51-59 - [c13]Mengdi Wang, Ji Liu, Ethan X. Fang:
Accelerating Stochastic Composition Optimization. NIPS 2016: 1714-1722 - [c12]Mengdi Wang, Yu-Ru Lin:
Link Prediction via Multi-hashing Framework. SBP-BRiMS 2016: 162-173 - [c11]Di Jin, Mengdi Wang, Yu-Ru Lin:
TeleLink: Link Prediction in Social Network Based on Multiplex Cohesive Structures. SBP-BRiMS 2016: 174-185 - [c10]Mengdi Wang, Ji Liu:
A stochastic compositional gradient method using Markov samples. WSC 2016: 702-713 - [i3]Yichen Chen, Mengdi Wang:
Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning. CoRR abs/1612.02516 (2016) - 2015
- [j3]Xiaohan Wang, Mengdi Wang, Yuantao Gu:
A Distributed Tracking Algorithm for Reconstruction of Graph Signals. IEEE J. Sel. Top. Signal Process. 9(4): 728-740 (2015) - [j2]Mengdi Wang, Dimitri P. Bertsekas:
Incremental constraint projection methods for variational inequalities. Math. Program. 150(2): 321-363 (2015) - [c9]Qian Fu, Zhongke Wu, Xiang Ying, Mengdi Wang, Xia Zheng, Mingquan Zhou:
Writing Chinese Calligraphy on Arbitrary Surfaces. CW 2015: 90-97 - [c8]Bo Li, Mengdi Wang, Yongxin Zhao, Geguang Pu, Huibiao Zhu, Fu Song:
Modeling and Verifying Google File System. HASE 2015: 207-214 - [c7]Jialin Liu, Yuantao Gu, Mengdi Wang:
Averaging random projection: A fast online solution for large-scale constrained stochastic optimization. ICASSP 2015: 3586-3590 - [c6]Mengdi Wang, Jing Yu, Weidong Sun:
Group-based hyperspectral image denoising using low rank representation. ICIP 2015: 1623-1627 - [i2]Xiaohan Wang, Mengdi Wang, Yuantao Gu:
A Distributed Tracking Algorithm for Reconstruction of Graph Signals. CoRR abs/1502.02973 (2015) - [i1]Mengdi Wang, Yichen Chen, Jialin Liu, Yuantao Gu:
Random Multi-Constraint Projection: Stochastic Gradient Methods for Convex Optimization with Many Constraints. CoRR abs/1511.03760 (2015) - 2014
- [j1]Mengdi Wang, Dimitri P. Bertsekas:
Stabilization of Stochastic Iterative Methods for Singular and Nearly Singular Linear Systems. Math. Oper. Res. 39(1): 1-30 (2014) - [c5]Yuantao Gu, Mengdi Wang:
Learning distributed jointly sparse systems by collaborative LMS. ICASSP 2014: 7228-7232 - [c4]Mengdi Wang, Yunjian Xu, Yuntao Gu:
Multi-task nonconvex optimization with total budget constraint: A distributed algorithm using Monte Carlo estimates. DSP 2014: 793-796 - [c3]Mengdi Wang, Bo Li, Yongxin Zhao, Geguang Pu:
Formalizing Google File System. PRDC 2014: 190-191 - 2013
- [b1]Mengdi Wang:
Stochastic methods for large-scale linear problems, variational inequalities, and convex optimization. Massachusetts Institute of Technology, Cambridge, MA, USA, 2013 - [c2]Dingxian Wang, Xiao Liu, Mengdi Wang:
A DT-SVM Strategy for Stock Futures Prediction with Big Data. CSE 2013: 1005-1012 - 2011
- [c1]Mengdi Wang, Beryl Plimmer, Paul Schmieder, Gem Stapleton, Peter Rodgers, Aidan J. Delaney:
SketchSet: Creating Euler diagrams using pen or mouse. VL/HCC 2011: 75-82
Coauthor Index
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