Peizhong Ju - RankMe

49 papers A* 13B 3Journal 26Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An LP-based Sampling Policy for Multi-Armed Bandits with Side-Observations and Stochastic Availability. CoRR Ashutosh Soni, Peizhong Ju, Atilla Eryilmaz, Ness B. Shroff
2026	—	`conf`	Evaluating Sparse Autoencoders for Monosemantic Representation. EACL (Findings) Moghis Fereidouni, Muhammad Umair Haider, Peizhong Ju, A. B. Siddique
2026	J	`jnl`	Flow Matching for Offline Reinforcement Learning with Discrete Actions. CoRR Fairoz Nower Khan, Nabuat Zaman Nahim, Ruiquan Huang, Haibo Yang, Peizhong Ju
2026	J	`jnl`	Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution. Trans. Mach. Learn. Res. Muhammad Umair Haider, Hammad Rizwan, Hassan Sajjad, Peizhong Ju, A. B. Siddique
2026	J	`jnl`	Provable Last-Iterate Convergence for Multi-Objective Safe LLM Alignment via Optimistic Primal-Dual. CoRR Yining Li, Peizhong Ju, Ness B. Shroff
2025	J	`jnl`	BeST - A Novel Source Selection Metric for Transfer Learning. CoRR Ashutosh Soni, Peizhong Ju, Atilla Eryilmaz, Ness B. Shroff
2025	A*	`conf`	Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach. ICLR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2025	J	`jnl`	Evaluating Sparse Autoencoders for Monosemantic Representation. CoRR Moghis Fereidouni, Muhammad Umair Haider, Peizhong Ju, A. B. Siddique
2025	A*	`conf`	FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation. ICML Srijith Nair, Michael Lin, Peizhong Ju, Amirreza Talebi, Elizabeth Serena Bentley, Jia Liu
2025	J	`jnl`	FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation. CoRR Srijith Nair, Michael Lin, Amirreza Talebi, Peizhong Ju, Elizabeth S. Bentley, Jia Liu
2025	A*	`conf`	How to Find the Exact Pareto Front for Multi-Objective MDPs? ICLR Yining Li, Peizhong Ju, Ness B. Shroff
2025	J	`jnl`	Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution. CoRR Muhammad Umair Haider, Hammad Rizwan, Hassan Sajjad, Peizhong Ju, A. B. Siddique
2025	J	`jnl`	Optimal Parallel Scheduling under Concave Speedup Functions. CoRR Chengzhang Li, Peizhong Ju, Atilla Eryilmaz, Ness B. Shroff
2025	A*	`conf`	PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization. AAAI Mingjing Xu, Peizhong Ju, Jia Liu, Haibo Yang
2025	A*	`conf`	Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers. ICLR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2025	B	`conf`	Two Levels Are All You Need: Simplifying Data Compression for Timely Edge Classification. MobiHoc Chengzhang Li, Peizhong Ju, Atilla Eryilmaz, Ness B. Shroff
2025	A*	`conf`	Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective. ICML Junze Deng, Qinhang Wu, Peizhong Ju, Sen Lin, Yingbin Liang, Ness B. Shroff
2025	J	`jnl`	Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective. CoRR Junze Deng, Qinhang Wu, Peizhong Ju, Sen Lin, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	AI-EDGE: An NSF AI institute for future edge networks and distributed intelligence. AI Mag. Peizhong Ju, Chengzhang Li, Yingbin Liang, Ness B. Shroff
2024	A*	`conf`	Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning. ICLR Peizhong Ju, Arnob Ghosh, Ness B. Shroff
2024	A*	`conf`	Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping. ICLR Yining Li, Peizhong Ju, Ness B. Shroff
2024	B	`conf`	Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? MobiHoc Peizhong Ju, Haibo Yang, Jia Liu, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? CoRR Peizhong Ju, Haibo Yang, Jia Liu, Yingbin Liang, Ness B. Shroff
2024	B	`conf`	Efficient Multi-dimensional Compression for Network-edge Classification. MobiHoc Chengzhang Li, Peizhong Ju, Atilla Eryilmaz, Ness B. Shroff
2024	J	`jnl`	How to Find the Exact Pareto Front for Multi-Objective MDPs? CoRR Yining Li, Peizhong Ju, Ness B. Shroff
2024	J	`jnl`	Non-asymptotic Convergence of Discrete-time Diffusion Models: New Approach and Improved Rate. CoRR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization. CoRR Mingjing Xu, Peizhong Ju, Jia Liu, Haibo Yang
2024	J	`jnl`	Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers. CoRR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning. CoRR Peizhong Ju, Arnob Ghosh, Ness B. Shroff
2023	J	`jnl`	Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping. CoRR Yining Li, Peizhong Ju, Ness B. Shroff
2023	J	`jnl`	Generalization Performance of Transfer Learning: Overparameterized and Underparameterized Regimes. CoRR Peizhong Ju, Sen Lin, Mark S. Squillante, Yingbin Liang, Ness B. Shroff
2023	A*	`conf`	Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning. ICLR Peizhong Ju, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning. CoRR Peizhong Ju, Yingbin Liang, Ness B. Shroff
2023	A*	`conf`	Theory on Forgetting and Generalization of Continual Learning. ICML Sen Lin, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Theory on Forgetting and Generalization of Continual Learning. CoRR Sen Lin, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2022	—	`conf`	Distribution-level markets under high renewable energy penetration. e-Energy Peizhong Ju, Xiaojun Lin, Jianwei Huang
2022	A*	`conf`	On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model. NeurIPS Peizhong Ju, Xiaojun Lin, Ness B. Shroff
2022	J	`jnl`	On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model. CoRR Peizhong Ju, Xiaojun Lin, Ness B. Shroff
2022	—	`conf`	Understanding the Generalization Power of Overfitted NTK Models: 3-layer vs. 2-layer (Extended Abstract). Allerton Peizhong Ju, Xiaojun Lin, Ness B. Shroff
2021	A*	`conf`	On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models. ICML Peizhong Ju, Xiaojun Lin, Ness B. Shroff
2021	J	`jnl`	On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models. CoRR Peizhong Ju, Xiaojun Lin, Ness B. Shroff
2020	A*	`conf`	Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree. NeurIPS Peizhong Ju, Xiaojun Lin, Jia Liu
2020	J	`jnl`	Overfitting Can Be Harmless for Basis Pursuit: Only to a Degree. CoRR Peizhong Ju, Xiaojun Lin, Jia Liu
2018	J	`jnl`	Achievable-Rate-Enhancing Self-Interference Cancellation for Full-Duplex Communications. IEEE Trans. Wirel. Commun. Peizhong Ju, Miaowen Wen, Xiang Cheng, Liuqing Yang
2018	—	`conf`	Adversarial Attacks to Distributed Voltage Control in Power Distribution Networks with DERs. e-Energy Peizhong Ju, Xiaojun Lin
2017	J	`jnl`	Generalized Spatial Modulation With Transmit Antenna Grouping for Massive MIMO. IEEE Access Weilin Qu, Meng Zhang, Xiang Cheng, Peizhong Ju
2017	—	`conf`	Generalized spatial modulation with transmit antenna grouping for massive MIMO. ICC Peizhong Ju, Meng Zhang, Xiang Cheng, Liuqing Yang
2016	—	`conf`	Generalized spatial modulation with transmit antenna grouping for correlated channels. ICC Peizhong Ju, Meng Zhang, Xiang Cheng, Cheng-Xiang Wang, Liuqing Yang
2015	—	`conf`	An effective self-interference cancellation scheme for spatial modulated full duplex systems. ICC Peizhong Ju, Miaowen Wen, Xiang Cheng, Liuqing Yang