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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
[j61]Hui Huang, Di Xiao, Mengdi Wang, Jia Liang, Min Li, Lvjun Chen, Yanqi Liu:
Fog-driven communication-efficient and privacy-preserving federated learning based on compressed sensing. Comput. Networks 259: 111043 (2025)- [j60]Mengdi Wang
, Matthew Cong, Bo Zhu:
An interface tracking method with triangle edge cuts. J. Comput. Phys. 520: 113504 (2025) - 2024
- [j59]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) - [j58]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) - [j57]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) - [j56]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) - [j55]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) - [j54]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) - [j53]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) - [j52]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) - [j51]Xue Tan, Di Xiao, Hui Huang, Mengdi Wang, Min Li:
Hierarchically Fair and Differentially Private Federated Learning in Industrial IoT Based on Compressed Sensing With Adaptive-Thresholding Sparsification. IEEE Trans. Ind. Informatics 20(12): 13731-13740 (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) - [c124]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 - [c123]Mengdi Wang, Anna Bodonhelyi, Efe Bozkir, Enkelejda Kasneci:
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients. AAAI 2024: 15546-15554 - [c122]Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal:
Visual Adversarial Examples Jailbreak Aligned Large Language Models. AAAI 2024: 21527-21536 - [c121]Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang:
Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis. AISTATS 2024: 2737-2745 - [c120]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 - [c119]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 - [c118]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 - [c117]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 - [c116]Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai:
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight. ICLR 2024 - [c115]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 - [c114]Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang:
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling. ICML 2024 - [c113]Alec Koppel, Sujay Bhatt, Jiacheng Guo, Joe Eappen, Mengdi Wang, Sumitra Ganesh:
Information-Directed Pessimism for Offline Reinforcement Learning. ICML 2024 - [c112]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 - [c111]Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei:
Theoretical insights for diffusion guidance: A case study for Gaussian mixture models. ICML 2024 - [c110]Lei Zhao, Mengdi Wang, Yu Bai:
Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective. ICML 2024 - [c109]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 - [c108]Shuhua Yang, Hui Yuan, Xiaoying Zhang, Mengdi Wang, Hong Zhang, Huazheng Wang:
Conversational Dueling Bandits in Generalized Linear Models. KDD 2024: 3806-3817 - [c107]Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang:
A Theoretical Perspective for Speculative Decoding Algorithm. NeurIPS 2024 - [c106]Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, Furong Huang:
Transfer Q-star : Principled Decoding for LLM Alignment. NeurIPS 2024 - [c105]Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan:
Global Convergence in Training Large-Scale Transformers. NeurIPS 2024 - [c104]Yingqing Guo, Hui Yuan, Yukang Yang, Minshuo Chen, Mengdi Wang:
Gradient Guidance for Diffusion Models: An Optimization Perspective. NeurIPS 2024 - [c103]Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup:
Offline Multitask Representation Learning for Reinforcement Learning. NeurIPS 2024 - [c102]Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang:
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context. NeurIPS 2024 - [c101]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. NeurIPS 2024 - [c100]Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang:
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. NeurIPS 2024 - [c99]Zaixi Zhang, Mengdi Wang, Qi Liu:
FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling. NeurIPS 2024 - [i139]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) - [i138]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) - [i137]Mengdi Wang, Anna Bodonhelyi, Efe Bozkir, Enkelejda Kasneci:
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients. CoRR abs/2401.12012 (2024) - [i136]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) - [i135]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) - [i134]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) - [i133]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) - [i132]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) - [i131]Zihao Li, Hui Lan, Vasilis Syrgkanis, Mengdi Wang, Masatoshi Uehara:
Regularized DeepIV with Model Selection. CoRR abs/2403.04236 (2024) - [i130]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) - [i129]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) - [i128]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) - [i127]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) - [i126]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) - [i125]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) - [i124]Yingqing Guo, Hui Yuan, Yukang Yang, Minshuo Chen, Mengdi Wang:
Gradient Guidance for Diffusion Models: An Optimization Perspective. CoRR abs/2404.14743 (2024) - [i123]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) - [i122]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) - [i121]Kaixuan Huang, Xudong Guo, Mengdi Wang:
SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths. CoRR abs/2405.19715 (2024) - [i120]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) - [i119]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) - [i118]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) - [i117]Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang:
Provable Statistical Rates for Consistency Diffusion Models. CoRR abs/2406.16213 (2024) - [i116]Jibang Wu, Siyu Chen, Mengdi Wang, Huazheng Wang, Haifeng Xu:
Contractual Reinforcement Learning: Pulling Arms with Invisible Hands. CoRR abs/2407.01458 (2024) - [i115]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) - [i114]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) - [i113]Shuhua Yang, Hui Yuan, Xiaoying Zhang, Mengdi Wang, Hong Zhang, Huazheng Wang:
Conversational Dueling Bandits in Generalized Linear Models. CoRR abs/2407.18488 (2024) - [i112]Binshuai Wang, Qiwei Di, Ming Yin, Mengdi Wang, Quanquan Gu, Peng Wei:
Relative-Translation Invariant Wasserstein Distance. CoRR abs/2409.02416 (2024) - [i111]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) - [i110]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) - [i109]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) - [i108]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) - [i107]Mengdi Wang, Matthew Cong, Bo Zhu:
An Interface Tracking Method with Triangle Edge Cuts. CoRR abs/2410.11073 (2024) - [i106]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) - [i105]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) - [i104]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) - [i103]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) - [i102]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) - [i101]Zaixi Zhang, Ruofan Jin, Kaidi Fu, Le Cong, Marinka Zitnik, Mengdi Wang:
FoldMark: Protecting Protein Generative Models with Watermarking. CoRR abs/2410.20354 (2024) - [i100]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) - [i99]Ming Yin, Minshuo Chen, Kaixuan Huang, Mengdi Wang:
A Theoretical Perspective for Speculative Decoding Algorithm. CoRR abs/2411.00841 (2024) - [i98]Kadir Burak Buldu, Süleyman Özdel, Ka Hei Carrie Lau, Mengdi Wang, Daniel Saad, Sofie Schönborn, Auxane Boch, Enkelejda Kasneci, Efe Bozkir:
CUIfy the XR: An Open-Source Package to Embed LLM-powered Conversational Agents in XR. CoRR abs/2411.04671 (2024) - [i97]Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang:
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context. CoRR abs/2411.10830 (2024) - [i96]Soumya Suvra Ghosal, Souradip Chakraborty, Vaibhav Singh, Tianrui Guan, Mengdi Wang, Ahmad Beirami, Furong Huang, Alvaro Velasquez, Dinesh Manocha, Amrit Singh Bedi:
Immune: Improving Safety Against Jailbreaks in Multi-modal LLMs via Inference-Time Alignment. CoRR abs/2411.18688 (2024) - [i95]James Beetham, Souradip Chakraborty, Mengdi Wang, Furong Huang, Amrit Singh Bedi, Mubarak Shah:
LIAR: Leveraging Alignment (Best-of-N) to Jailbreak LLMs in Seconds. CoRR abs/2412.05232 (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]