Jingzhao Zhang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 52

Top Topics

Text Generation

Stochastic Optimization Algorithm

Diffusion Models

Nearest Neighbor Classifiers

Top Venues

Publications

Lesi Chen, Jing Xu, Jingzhao Zhang
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis. COLT (2024)
Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang
A Quadratic Synchronization Rule for Distributed Deep Learning. ICLR (2024)
Jingwei Li, Jing Dong, Tianxing He, Jingzhao Zhang
Towards Black-Box Membership Inference Attack for Diffusion Models. CoRR (2024)
Xiang Cheng, Jingzhao Zhang, Suvrit Sra
Efficient Sampling on Riemannian Manifolds via Langevin MCMC. CoRR (2024)
Jing Xu, Jingzhao Zhang
Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning. CoRR (2024)
Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions. CoRR (2023)
Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective. NeurIPS (2023)
Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang
Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization. CoRR (2023)
Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu
Iteratively Learn Diverse Strategies with State Distance Information. CoRR (2023)
Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang
A Quadratic Synchronization Rule for Distributed Deep Learning. CoRR (2023)
Jingwei Li, Jing Dong, Baoxiang Wang, Jingzhao Zhang
Online Control with Adversarial Disturbance for Continuous-time Linear Systems. CoRR (2023)
Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions. NeurIPS (2023)
Lesi Chen, Yaohua Ma, Jingzhao Zhang
Near-Optimal Fully First-Order Algorithms for Finding Stationary Points in Bilevel Optimization. CoRR (2023)
Pengkun Yang, Jingzhao Zhang
Two Phases of Scaling Laws for Nearest Neighbor Classifiers. CoRR (2023)
Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra
Sion's Minimax Theorem in Geodesic Metric Spaces and a Riemannian Extragradient Algorithm. SIAM J. Optim. 33 (4) (2023)
Kaiyue Wen, Jiaye Teng, Jingzhao Zhang
Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models. ICLR (2023)
Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu
Iteratively Learn Diverse Strategies with State Distance Information. NeurIPS (2023)
Lesi Chen, Jing Xu, Jingzhao Zhang
On Bilevel Optimization without Lower-level Strong Convexity. CoRR (2023)
Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra
Minimax in Geodesic Metric Spaces: Sion's Theorem and Algorithms. CoRR (2022)
Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra
Understanding the unstable convergence of gradient descent. CoRR (2022)
Haowei He, Jingzhao Zhang, Yanan Wang, Shaobo Huang, Chen Wang, Yang Zhang, Dongxu Guo, Guannan He, Minggao Ouyang
Detecting Electric Vehicle Battery Failure via Dynamic-VAE. CoRR (2022)
Xiang Cheng, Jingzhao Zhang, Suvrit Sra
Efficient Sampling on Riemannian Manifolds via Langevin MCMC. NeurIPS (2022)
Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra
Understanding the unstable convergence of gradient descent. ICML (2022)
Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity. ICML (2022)
Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang
Online Policy Optimization for Robust MDP. CoRR (2022)
Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective. ICML (2022)
Kaiyue Wen, Jiaye Teng, Jingzhao Zhang
Realistic Deep Learning May Not Fit Benignly. CoRR (2022)
Zhiyong Wang, Jingzhao Zhang, Yaran Yu, Jian Liu, Wei Liu, Na Jiang, Donge Guo
Monitoring, Analyzing, and Modeling for Single Subsidence Basin in Coal Mining Areas Based on SAR Interferometry with L-Band Data. Sci. Program. 2021 (2021)
Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie
On Convergence of Training Loss Without Reaching Stationary Points. CoRR (2021)
Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang
Fast Federated Learning in the Presence of Arbitrary Device Unavailability. CoRR (2021)
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Provably Efficient Algorithms for Multi-Objective Competitive RL. ICML (2021)
Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang
Fast Federated Learning in the Presence of Arbitrary Device Unavailability. NeurIPS (2021)
Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization. CoRR (2021)
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Provably Efficient Algorithms for Multi-Objective Competitive RL. CoRR (2021)
Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
Coping with Label Shift via Distributionally Robust Optimisation. ICLR (2021)
Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass
Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? EMNLP (1) (2021)
Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization. NeurIPS (2021)
Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra
Why are Adaptive Methods Good for Attention Models? NeurIPS (2020)
Jingzhao Zhang, Hongzhou Lin, Suvrit Sra, Ali Jadbabaie
On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions. CoRR (2020)
Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie
Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity. ICLR (2020)
Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie
Stochastic Optimization with Non-stationary Noise. CoRR (2020)
Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
Coping with Label Shift via Distributionally Robust Optimisation. CoRR (2020)
Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie
Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions. ICML (2020)
Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie
Analysis of Gradient Clipping and Adaptive Scaling with a Relaxed Smoothness Condition. CoRR (2019)
Jingzhao Zhang, César A. Uribe, Aryan Mokhtari, Ali Jadbabaie
Achieving Acceleration in Distributed Optimization via Direct Discretization of the Heavy-Ball ODE. ACC (2019)
Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass
Quantifying Exposure Bias for Neural Language Generation. CoRR (2019)
Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra
Why ADAM Beats SGD for Attention Models. CoRR (2019)
Jingzhao Zhang, Suvrit Sra, Ali Jadbabaie
Acceleration in First Order Quasi-strongly Convex Optimization by ODE Discretization. CDC (2019)
Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie
Direct Runge-Kutta Discretization Achieves Acceleration. CoRR (2018)
Jingzhao Zhang, Hongyi Zhang, Suvrit Sra
R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate. CoRR (2018)
Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie
Direct Runge-Kutta Discretization Achieves Acceleration. NeurIPS (2018)
Lu Mi, Macheng Shen, Jingzhao Zhang
A Probe Towards Understanding GAN and VAE Models. CoRR (2018)