Zhi-Ming Ma

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 46

Top Topics

Convergence Analysis

Top Venues

Publications

Zhi-Ming Ma, Liuquan Yao, Shuai Yuan, Huazi Zhang
Entropic Conditional Central Limit Theorem and Hadamard Compression. CoRR (2024)
Shikun Feng, Yuyan Ni, Yanyan Lan, Zhi-Ming Ma, Wei-Ying Ma
Fractional Denoising for 3D Molecular Pre-training. ICML (2023)
Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method. CoRR (2023)
Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma
A new perspective on building efficient and expressive 3D equivariant graph neural networks. CoRR (2023)
Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models. NeurIPS (2023)
Bohan Wang, Huishuai Zhang, Zhi-Ming Ma, Wei Chen
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. CoRR (2023)
Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhi-Ming Ma
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. ICML (2023)
Chongchong Li, Yue Wang, Zhi-Ming Ma, Yuting Liu
How to Select the Appropriate One from the Trained Models for Model-Based OPE. CICAI (2) (2023)
Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models. CoRR (2023)
Shikun Feng, Yuyan Ni, Yanyan Lan, Zhi-Ming Ma, Wei-Ying Ma
Fractional Denoising for 3D Molecular Pre-training. CoRR (2023)
Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng
Power-law Dynamic arising from machine learning. CoRR (2023)
Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. NeurIPS (2023)
Shengchao Liu, weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. NeurIPS (2023)
Rui Zhang, Qi Meng, Zhi-Ming Ma
Deciphering and integrating invariants for neural operator learning with various physical mechanisms. CoRR (2023)
Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. ICML (2023)
Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
Breaking Correlation Shift via Conditional Invariant Regularizer. ICLR (2023)
Peiyan Hu, Yue Wang, Zhi-Ming Ma
Better Neural PDE Solvers Through Data-Free Mesh Movers. CoRR (2023)
Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma
A new perspective on building efficient and expressive 3D equivariant graph neural networks. NeurIPS (2023)
Rui Zhang, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu
Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation. CoRR (2023)
Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu
Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations. CoRR (2022)
Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
Gradient Information Matters in Policy Optimization by Back-propagating through Model. ICLR (2022)
Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu
Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. CoRR (2022)
Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen
Provable Adaptivity in Adam. CoRR (2022)
Yimeng Chen, Ruibin Xiong, Zhi-Ming Ma, Yanyan Lan
When Does Group Invariant Learning Survive Spurious Correlations? NeurIPS (2022)
Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma
Characterization of Excess Risk for Locally Strongly Convex Population Risk. NeurIPS (2022)
Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
Improved OOD Generalization via Conditional Invariant Regularizer. CoRR (2022)
Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS (2022)
Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma
Momentum Doesn't Change the Implicit Bias. CoRR (2021)
Ruibin Xiong, Yimeng Chen, Liang Pang, Xueqi Cheng, Zhi-Ming Ma, Yanyan Lan
Uncertainty Calibration for Ensemble-Based Debiasing Methods. NeurIPS (2021)
Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma
Towards Accelerating Training of Batch Normalization: A Manifold Perspective. CoRR (2021)
Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
Improved OOD Generalization via Adversarial Training and Pre-training. CoRR (2021)
Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. ICLR (2021)
Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. CoRR (2021)
Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics. CoRR (2021)
Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
BN-invariant sharpness regularizes the training model to better generalization. CoRR (2021)
Yue Wang, Yuting Liu, Zhi-Ming Ma
The scale-invariant space for attention layer in neural network. Neurocomputing 392 (2020)
Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Dynamic of Stochastic Gradient Descent with State-Dependent Noise. CoRR (2020)
Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma
Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape. CoRR (2020)
Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Target transfer Q-learning and its convergence analysis. Neurocomputing 392 (2020)
Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin
Off-policy Learning for Multiple Loggers. CoRR (2019)
Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin
Off-policy Learning for Multiple Loggers. KDD (2019)
Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. ICLR (Poster) (2019)
Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
BN-invariant Sharpness Regularizes the Training Model to Better Generalization. IJCAI (2019)
Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu
Convergence analysis of distributed stochastic gradient descent with shuffling. Neurocomputing 337 (2019)
Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
Positively Scale-Invariant Flatness of ReLU Neural Networks. CoRR (2019)
Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting. CoRR (2018)