Jingzhao Zhang

According to our database, Jingzhao Zhang authored at least 40 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Sion's Minimax Theorem in Geodesic Metric Spaces and a Riemannian Extragradient Algorithm.

Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra

SIAM J. Optim., December, 2023

A Quadratic Synchronization Rule for Distributed Deep Learning.

Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang

CoRR, 2023

Two Phases of Scaling Laws for Nearest Neighbor Classifiers.

Pengkun Yang, Jingzhao Zhang

CoRR, 2023

Near-Optimal Fully First-Order Algorithms for Finding Stationary Points in Bilevel Optimization.

Lesi Chen, Yaohua Ma, Jingzhao Zhang

CoRR, 2023

Online Control with Adversarial Disturbance for Continuous-time Linear Systems.

Jingwei Li, Jing Dong, Baoxiang Wang, Jingzhao Zhang

CoRR, 2023

Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization.

Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang

CoRR, 2023

On Bilevel Optimization without Lower-level Strong Convexity.

Lesi Chen, Jing Xu, Jingzhao Zhang

CoRR, 2023

On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective.

Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Iteratively Learn Diverse Strategies with State Distance Information.

Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions.

Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models.

Kaiyue Wen, Jiaye Teng, Jingzhao Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Optimization Theory and Machine Learning Practice: Mind the Gap.

Jingzhao Zhang

PhD thesis, 2022

Online Policy Optimization for Robust MDP.

Jing Dong, Jingwei Li, Baoxiang Wang, Jingzhao Zhang

CoRR, 2022

Realistic Deep Learning May Not Fit Benignly.

Kaiyue Wen, Jiaye Teng, Jingzhao Zhang

CoRR, 2022

Minimax in Geodesic Metric Spaces: Sion's Theorem and Algorithms.

Peiyuan Zhang, Jingzhao Zhang, Suvrit Sra

CoRR, 2022

Detecting Electric Vehicle Battery Failure via Dynamic-VAE.

Haowei He, Jingzhao Zhang, Yanan Wang, Shaobo Huang, Chen Wang, Yang Zhang, Dongxu Guo, Guannan He, Minggao Ouyang

CoRR, 2022

Efficient Sampling on Riemannian Manifolds via Langevin MCMC.

Xiang Cheng, Jingzhao Zhang, Suvrit Sra

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective.

Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie

Proceedings of the International Conference on Machine Learning, 2022

Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity.

Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie

Proceedings of the International Conference on Machine Learning, 2022

Understanding the unstable convergence of gradient descent.

Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra

Proceedings of the International Conference on Machine Learning, 2022

2021

Monitoring, Analyzing, and Modeling for Single Subsidence Basin in Coal Mining Areas Based on SAR Interferometry with L-Band Data.

Zhiyong Wang, Jingzhao Zhang, Yaran Yu, Jian Liu, Wei Liu, Na Jiang, Donge Guo

Sci. Program., 2021

On Convergence of Training Loss Without Reaching Stationary Points.

Jingzhao Zhang, Haochuan Li, Suvrit Sra, Ali Jadbabaie

CoRR, 2021

Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization.

Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fast Federated Learning in the Presence of Arbitrary Device Unavailability.

Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provably Efficient Algorithms for Multi-Objective Competitive RL.

Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra

Proceedings of the 38th International Conference on Machine Learning, 2021

Coping with Label Shift via Distributionally Robust Optimisation.

Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra

Proceedings of the 9th International Conference on Learning Representations, 2021

Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation?

Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Stochastic Optimization with Non-stationary Noise.

Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie

CoRR, 2020

On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions.

Jingzhao Zhang, Hongzhou Lin, Suvrit Sra, Ali Jadbabaie

CoRR, 2020

Why are Adaptive Methods Good for Attention Models?

Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions.

Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie

Proceedings of the 37th International Conference on Machine Learning, 2020

Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity.

Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Why ADAM Beats SGD for Attention Models.

Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra

CoRR, 2019

Analysis of Gradient Clipping and Adaptive Scaling with a Relaxed Smoothness Condition.

Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie

CoRR, 2019

Quantifying Exposure Bias for Neural Language Generation.

Tianxing He, Jingzhao Zhang, Zhiming Zhou, James R. Glass

CoRR, 2019

Acceleration in First Order Quasi-strongly Convex Optimization by ODE Discretization.

Jingzhao Zhang, Suvrit Sra, Ali Jadbabaie

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Achieving Acceleration in Distributed Optimization via Direct Discretization of the Heavy-Ball ODE.

Jingzhao Zhang, César A. Uribe, Aryan Mokhtari, Ali Jadbabaie

Proceedings of the 2019 American Control Conference, 2019

2018

A Probe Towards Understanding GAN and VAE Models.

Lu Mi, Macheng Shen, Jingzhao Zhang

CoRR, 2018

R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate.

Jingzhao Zhang, Hongyi Zhang, Suvrit Sra

CoRR, 2018

Direct Runge-Kutta Discretization Achieves Acceleration.

Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018