Jingzhao Zhang

84 papers A* 29A 2C 1Journal 49Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization. CoRR Jingwei Li, Xinran Gu, Jingzhao Zhang
2025	J	`jnl`	Data Mixing Can Induce Phase Transitions in Knowledge Acquisition. CoRR Xinran Gu, Kaifeng Lyu, Jiazheng Li, Jingzhao Zhang
2025	A*	`conf`	Fast and Multiphase Rates for Nearest Neighbor Classifiers. COLT Pengkun Yang, Jingzhao Zhang
2025	J	`jnl`	Faster Gradient Methods for Highly-smooth Stochastic Bilevel Optimization. CoRR Lesi Chen, Junru Li, Jingzhao Zhang
2025	J	`jnl`	Finite Sample Analyses for Continuous-time Linear Systems: System Identification and Online Control. CoRR Hongyi Zhou, Jingwei Li, Jingzhao Zhang
2025	A*	`conf`	From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency. ICLR Kaiyue Wen, Huaqing Zhang, Hongzhou Lin, Jingzhao Zhang
2025	A	`conf`	Generalization Lower Bounds for GD and SGD in Smooth Stochastic Convex Optimization. AISTATS Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang
2025	J	`jnl`	Multitask Battery Management with Flexible Pretraining. CoRR Hong Lu, Jiali Chen, Jingzhao Zhang, Guannan He, Xuebing Han, Minggao Ouyang
2025	J	`jnl`	Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles. J. Mach. Learn. Res. Lesi Chen, Yaohua Ma, Jingzhao Zhang
2025	J	`jnl`	NeuralDB: Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database. CoRR Weizhi Fei, Hao Shi, Jing Xu, Jingchen Peng, Jiazheng Li, Jingzhao Zhang, Bo Bai, Wei Han, Zhenyuan Chen, Xueyan Niu
2025	J	`jnl`	On the Condition Number Dependency in Bilevel Optimization. CoRR Lesi Chen, Jingzhao Zhang
2025	J	`jnl`	PiERN: Token-Level Routing for Integrating High-Precision Computation and Reasoning. CoRR Hengbo Xiao, Jingyuan Fan, Xin Tong, Jingzhao Zhang, Chao Lu, Guannan He
2025	J	`jnl`	QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation. CoRR Jiazheng Li, Hong Lu, Kaiyue Wen, Zaiwen Yang, Jiaxuan Gao, Hongzhou Lin, Yi Wu, Jingzhao Zhang
2025	A*	`conf`	Scalable Model Merging with Progressive Layer-wise Distillation. ICML Jing Xu, Jiazheng Li, Jingzhao Zhang
2025	J	`jnl`	Scalable Model Merging with Progressive Layer-wise Distillation. CoRR Jing Xu, Jiazheng Li, Jingzhao Zhang
2025	A*	`conf`	Second-Order Min-Max Optimization with Lazy Hessians. ICLR Lesi Chen, Chengchang Liu, Jingzhao Zhang
2025	A*	`conf`	Solving Convex-Concave Problems with 풪(ε COLT Lesi Chen, Chengchang Liu, Luo Luo, Jingzhao Zhang
2025	J	`jnl`	Solving Convex-Concave Problems with 𝒪(ε CoRR Lesi Chen, Chengchang Liu, Luo Luo, Jingzhao Zhang
2025	J	`jnl`	Task Generalization With AutoRegressive Compositional Structure: Can Learning From CoRR Amirhesam Abedsoltan, Huaqing Zhang, Kaiyue Wen, Hongzhou Lin, Jingzhao Zhang, Mikhail Belkin
2025	A*	`conf`	Task Generalization with Autoregressive Compositional Structure: Can Learning from D Tasks Generalize to DT Tasks? ICML Amirhesam Abedsoltan, Huaqing Zhang, Kaiyue Wen, Hongzhou Lin, Jingzhao Zhang, Mikhail Belkin
2025	A*	`conf`	Towards Black-Box Membership Inference Attack for Diffusion Models. ICML Jingwei Li, Jing Dong, Tianxing He, Jingzhao Zhang
2025	A*	`conf`	Understanding Nonlinear Implicit Bias via Region Counts in Input Space. ICML Jingwei Li, Jing Xu, Zifan Wang, Huishuai Zhang, Jingzhao Zhang
2025	J	`jnl`	Understanding Nonlinear Implicit Bias via Region Counts in Input Space. CoRR Jingwei Li, Jing Xu, Zifan Wang, Huishuai Zhang, Jingzhao Zhang
2024	A*	`conf`	A Quadratic Synchronization Rule for Distributed Deep Learning. ICLR Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang
2024	J	`jnl`	Efficient Sampling on Riemannian Manifolds via Langevin MCMC. CoRR Xiang Cheng, Jingzhao Zhang, Suvrit Sra
2024	J	`jnl`	From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency. CoRR Kaiyue Wen, Huaqing Zhang, Hongzhou Lin, Jingzhao Zhang
2024	A*	`conf`	Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem. NeurIPS Huaqing Zhang, Lesi Chen, Jing Xu, Jingzhao Zhang
2024	J	`jnl`	Functionally Constrained Algorithm Solves Convex Simple Bilevel Problems. CoRR Huaqing Zhang, Lesi Chen, Jing Xu, Jingzhao Zhang
2024	A*	`conf`	On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis. COLT Lesi Chen, Jing Xu, Jingzhao Zhang
2024	A*	`conf`	Online Control with Adversarial Disturbance for Continuous-time Linear Systems. NeurIPS Jingwei Li, Jing Dong, Can Chang, Baoxiang Wang, Jingzhao Zhang
2024	A	`conf`	Online Policy Optimization for Robust Markov Decision Process. UAI Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang
2024	A*	`conf`	Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning. ICML Jing Xu, Jingzhao Zhang
2024	J	`jnl`	Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning. CoRR Jing Xu, Jingzhao Zhang
2024	J	`jnl`	Second-Order Min-Max Optimization with Lazy Hessians. CoRR Lesi Chen, Chengchang Liu, Jingzhao Zhang
2024	J	`jnl`	Time Series Prediction of Gas Emission in Coal Mining Face Based on Optimized Variational Mode Decomposition and SSA-LSTM. Sensors Jingzhao Zhang, Yuxin Cui, Zhenguo Yan, Yuxin Huang, Chenyu Zhang, Jinlong Zhang, Jiantao Guo, Fei Zhao
2024	J	`jnl`	Towards Black-Box Membership Inference Attack for Diffusion Models. CoRR Jingwei Li, Jing Dong, Tianxing He, Jingzhao Zhang
2023	J	`jnl`	A Quadratic Synchronization Rule for Distributed Deep Learning. CoRR Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang
2023	A*	`conf`	Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models. ICLR Kaiyue Wen, Jiaye Teng, Jingzhao Zhang
2023	A*	`conf`	Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions. NeurIPS Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu
2023	J	`jnl`	Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions. CoRR Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu
2023	A*	`conf`	Iteratively Learn Diverse Strategies with State Distance Information. NeurIPS Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu
2023	J	`jnl`	Iteratively Learn Diverse Strategies with State Distance Information. CoRR Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu
2023	J	`jnl`	Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization. CoRR Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang
2023	J	`jnl`	Near-Optimal Fully First-Order Algorithms for Finding Stationary Points in Bilevel Optimization. CoRR Lesi Chen, Yaohua Ma, Jingzhao Zhang
2023	J	`jnl`	On Bilevel Optimization without Lower-level Strong Convexity. CoRR Lesi Chen, Jing Xu, Jingzhao Zhang
2023	A*	`conf`	On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective. NeurIPS Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama
2023	J	`jnl`	Online Control with Adversarial Disturbance for Continuous-time Linear Systems. CoRR Jingwei Li, Jing Dong, Baoxiang Wang, Jingzhao Zhang
2023	J	`jnl`	Sion's Minimax Theorem in Geodesic Metric Spaces and a Riemannian Extragradient Algorithm. SIAM J. Optim. Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra
2023	J	`jnl`	Two Phases of Scaling Laws for Nearest Neighbor Classifiers. CoRR Pengkun Yang, Jingzhao Zhang
2022	A*	`conf`	Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity. ICML Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
2022	J	`jnl`	Detecting Electric Vehicle Battery Failure via Dynamic-VAE. CoRR Haowei He, Jingzhao Zhang, Yanan Wang, Shaobo Huang, Chen Wang, Yang Zhang, Dongxu Guo, Guannan He, Minggao Ouyang
2022	A*	`conf`	Efficient Sampling on Riemannian Manifolds via Langevin MCMC. NeurIPS Xiang Cheng, Jingzhao Zhang, Suvrit Sra
2022	J	`jnl`	Minimax in Geodesic Metric Spaces: Sion's Theorem and Algorithms. CoRR Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra
2022	A*	`conf`	Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective. ICML Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie
2022	J	`jnl`	Online Policy Optimization for Robust MDP. CoRR Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang
2022	—	`—`	Optimization Theory and Machine Learning Practice: Mind the Gap. Jingzhao Zhang
2022	J	`jnl`	Realistic Deep Learning May Not Fit Benignly. CoRR Kaiyue Wen, Jiaye Teng, Jingzhao Zhang
2022	A*	`conf`	Understanding the unstable convergence of gradient descent. ICML Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra
2022	J	`jnl`	Understanding the unstable convergence of gradient descent. CoRR Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra
2021	A*	`conf`	Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization. NeurIPS Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie
2021	J	`jnl`	Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization. CoRR Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie
2021	A*	`conf`	Coping with Label Shift via Distributionally Robust Optimisation. ICLR Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
2021	—	`conf`	Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? EMNLP (1) Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass
2021	A*	`conf`	Fast Federated Learning in the Presence of Arbitrary Device Unavailability. NeurIPS Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang
2021	J	`jnl`	Fast Federated Learning in the Presence of Arbitrary Device Unavailability. CoRR Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang
2021	J	`jnl`	Monitoring, Analyzing, and Modeling for Single Subsidence Basin in Coal Mining Areas Based on SAR Interferometry with L-Band Data. Sci. Program. Zhiyong Wang, Jingzhao Zhang, Yaran Yu, Jian Liu, Wei Liu, Na Jiang, Donge Guo
2021	J	`jnl`	On Convergence of Training Loss Without Reaching Stationary Points. CoRR Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie
2021	A*	`conf`	Provably Efficient Algorithms for Multi-Objective Competitive RL. ICML Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
2021	J	`jnl`	Provably Efficient Algorithms for Multi-Objective Competitive RL. CoRR Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
2020	A*	`conf`	Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions. ICML Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie
2020	J	`jnl`	Coping with Label Shift via Distributionally Robust Optimisation. CoRR Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
2020	J	`jnl`	On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions. CoRR Jingzhao Zhang, Hongzhou Lin, Suvrit Sra, Ali Jadbabaie
2020	J	`jnl`	Stochastic Optimization with Non-stationary Noise. CoRR Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
2020	A*	`conf`	Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity. ICLR Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie
2020	A*	`conf`	Why are Adaptive Methods Good for Attention Models? NeurIPS Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra
2019	—	`conf`	Acceleration in First Order Quasi-strongly Convex Optimization by ODE Discretization. CDC Jingzhao Zhang, Suvrit Sra, Ali Jadbabaie
2019	C	`conf`	Achieving Acceleration in Distributed Optimization via Direct Discretization of the Heavy-Ball ODE. ACC Jingzhao Zhang, César A. Uribe, Aryan Mokhtari, Ali Jadbabaie
2019	J	`jnl`	Analysis of Gradient Clipping and Adaptive Scaling with a Relaxed Smoothness Condition. CoRR Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie
2019	J	`jnl`	Quantifying Exposure Bias for Neural Language Generation. CoRR Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass
2019	J	`jnl`	Why ADAM Beats SGD for Attention Models. CoRR Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra
2018	J	`jnl`	A Probe Towards Understanding GAN and VAE Models. CoRR Lu Mi, Macheng Shen, Jingzhao Zhang
2018	A*	`conf`	Direct Runge-Kutta Discretization Achieves Acceleration. NeurIPS Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie
2018	J	`jnl`	Direct Runge-Kutta Discretization Achieves Acceleration. CoRR Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie
2018	J	`jnl`	R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate. CoRR Jingzhao Zhang, Hongyi Zhang, Suvrit Sra