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ORCIDZhiming Ma
Zhi-Ming Ma
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- affiliation: Academy of Mathematics and Systems Science, Chinese Academy of Sciences
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2020 – today
- 2024
[j18]Chongchong Li
, Yuting Liu, Zhi-Ming Ma:
Neural networks taking probability distributions as input: A framework for analyzing exchangeable networks. Neurocomputing 584: 127572 (2024)- [j17]Yuyan Ni, Shikun Feng, Xin Hong, Yuancheng Sun, Wei-Ying Ma, Zhi-Ming Ma, Qiwei Ye, Yanyan Lan:
Pre-training with fractional denoising to enhance molecular property prediction. Nat. Mac. Intell. 6(10): 1169-1178 (2024) - [j16]Zicheng Ye, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
On the Distribution of Weights Less Than 2wminin Polar Codes. IEEE Trans. Commun. 72(10): 5988-6000 (2024) - [j15]Zicheng Ye, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
Affine Automorphism Group of Polar Codes. IEEE Trans. Inf. Theory 70(9): 6280-6296 (2024) - [c61]Bowen Gao, Yinjun Jia, Yuanle Mo, Yuyan Ni, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan:
Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment. ICLR 2024 - [c60]Peiyan Hu, Yue Wang, Zhi-Ming Ma:
Better Neural PDE Solvers Through Data-Free Mesh Movers. ICLR 2024 - [c59]Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan:
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method. ICLR 2024 - [c58]Shikun Feng, Yuyan Ni, Minghao Li, Yanwen Huang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan:
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning. ICML 2024 - [c57]Bowen Gao, Minsi Ren, Yuyan Ni, Yanwen Huang, Bo Qiang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan:
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion. ICML 2024 - [c56]Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi:
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. ICML 2024 - [c55]Shuai Zhang, Chuan Zhou, Yang Aron Liu, Peng Zhang, Xixun Lin, Zhi-Ming Ma:
Neural Jump-Diffusion Temporal Point Processes. ICML 2024 - [c54]Zhicheng Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
Second-Order Identification Capacity of AWGN Channels. ISIT 2024: 309-314 - [c53]Liuquan Yao, Zhichao Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhi-Ming Ma:
New Partial Orders of Polar Codes for BMSC. ISIT 2024: 2192-2197 - [c52]Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen:
Provable Adaptivity of Adam under Non-uniform Smoothness. KDD 2024: 2960-2969 - [i68]Zhi-Ming Ma, Liuquan Yao, Shuai Yuan, Huazi Zhang:
Entropic Conditional Central Limit Theorem and Hadamard Compression. CoRR abs/2401.11383 (2024) - [i67]Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi:
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. CoRR abs/2402.15170 (2024) - [i66]Bowen Gao, Minsi Ren, Yuyan Ni, Yanwen Huang, Bo Qiang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan:
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion. CoRR abs/2403.12987 (2024) - [i65]Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen:
On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond. CoRR abs/2403.15146 (2024) - [i64]Liuquan Yao, Zhichao Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
New Partial Orders of Polar Codes for BMSC. CoRR abs/2404.06736 (2024) - [i63]Zhicheng Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
Second-Order Identification Capacity of AWGN Channels. CoRR abs/2404.13685 (2024) - [i62]Liuquan Yao, Shuai Yuan, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
Fundamental Bounds on Unequal Error Protection Codes. CoRR abs/2405.03288 (2024) - [i61]Shikun Feng, Yuyan Ni, Minghao Li, Yanwen Huang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan:
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning. CoRR abs/2405.10343 (2024) - [i60]Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu:
A Generative Approach to Control Complex Physical Systems. CoRR abs/2407.06494 (2024) - [i59]Yuyan Ni, Shikun Feng, Xin Hong, Yuancheng Sun, Wei-Ying Ma, Zhi-Ming Ma, Qiwei Ye, Yanyan Lan:
Pre-training with Fractional Denoising to Enhance Molecular Property Prediction. CoRR abs/2407.11086 (2024) - [i58]Haixin Wang, Yadi Cao, Zijie Huang, Yuxuan Liu, Peiyan Hu, Xiao Luo, Zezheng Song, Wanjia Zhao, Jilin Liu, Jinan Sun, Shikun Zhang, Long Wei, Yue Wang, Tailin Wu, Zhi-Ming Ma, Yizhou Sun:
Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey. CoRR abs/2408.12171 (2024) - [i57]Shikun Feng, Yuyan Ni, Yan Lu, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan:
UniGEM: A Unified Approach to Generation and Property Prediction for Molecules. CoRR abs/2410.10516 (2024) - [i56]Zhichao Liu, Zhiming Ma, Guiying Yan:
A Method to Reduce the Complexity of Computing the Complete Weight Distribution of Polar Codes. CoRR abs/2410.17872 (2024) - [i55]Zicheng Ye, Yuan Li, Zhichao Liu, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
On the Weight Spectrum of Rate-Compatible Polar Codes. CoRR abs/2410.19242 (2024) - [i54]Zhichao Liu, Liuquan Yao, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
Partial Orders of Sequential Rate-Matched Polar Codes. CoRR abs/2410.21661 (2024) - [i53]Liuquan Yao, Pei Yang, Zhichao Liu, Wenyan Li, Jianghua Liu, Zhi-Ming Ma:
Erlang Model for Multiple Data Streams (Full Version). CoRR abs/2411.00792 (2024) - 2023
- [j14]Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhiming Ma, Tie-Yan Liu:
Incorporating NODE with pre-trained neural differential operator for learning dynamics. Neurocomputing 528: 48-58 (2023) - [j13]Zhiming Ma, Dali Chen, Yilin Mo, Yue Chen, Yumin Zhang:
A Weakly Supervised Semantic Segmentation Method Based on Local Superpixel Transformation. Neural Process. Lett. 55(9): 12039-12060 (2023) - [c51]Shiqi Gong, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhiming Ma, Hao Ni, Tie-Yan Liu:
Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations. AAAI 2023: 7740-7747 - [c50]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: 285-297 - [c49]Bohan Wang, Huishuai Zhang, Zhiming Ma, Wei Chen:
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. COLT 2023: 161-190 - [c48]Shuai Yuan, Liuquan Yao, Yuan Li, Huazi Zhang, Jun Wang, Wen Tong, Zhiming Ma:
Lossless Analog Compression via Polarization. GLOBECOM 2023: 6995-7000 - [c47]Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma:
Breaking Correlation Shift via Conditional Invariant Regularizer. ICLR 2023 - [c46]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: 4623-4640 - [c45]Shikun Feng, Yuyan Ni, Yanyan Lan, Zhi-Ming Ma, Wei-Ying Ma:
Fractional Denoising for 3D Molecular Pre-training. ICML 2023: 9938-9961 - [c44]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: 21497-21526 - [c43]Yuan Li, Zicheng Ye, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
On the Weight Spectrum Improvement of Pre-transformed Reed-Muller Codes and Polar Codes. ISIT 2023: 2153-2158 - [c42]Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu:
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. NeurIPS 2023 - [c41]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 - [c40]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 - [c39]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 - [c38]Wenxuan Lang, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
Improved Finite-Length Bound of Gaussian Unsourced Multiple Access. WCNC 2023: 1-6 - [i52]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 abs/2302.05104 (2023) - [i51]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 abs/2304.04757 (2023) - [i50]Shengchao Liu, Weitao Du, Zhiming Ma, Hongyu Guo, Jian Tang:
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. CoRR abs/2305.18407 (2023) - [i49]Bohan Wang, Huishuai Zhang, Zhi-Ming Ma, Wei Chen:
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. CoRR abs/2305.18471 (2023) - [i48]Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhiming Ma:
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. CoRR abs/2306.02595 (2023) - [i47]Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhiming Ma, Omar Yaghi, Anima Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang:
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. CoRR abs/2306.09375 (2023) - [i46]Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng:
Power-law Dynamic arising from machine learning. CoRR abs/2306.09624 (2023) - [i45]Haoran Xiong, Zicheng Ye, Huazi Zhang, Jun Wang, Ke Liu, Dawei Yin, Guanghui Wang, Guiying Yan, Zhiming Ma:
Theoretical Bounds for the Size of Elementary Trapping Sets by Graphic Methods. CoRR abs/2307.02737 (2023) - [i44]Yuan Li, Zicheng Ye, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
On the Weight Spectrum Improvement of Pre-transformed Reed-Muller Codes and Polar Codes. CoRR abs/2307.06599 (2023) - [i43]Shikun Feng, Yuyan Ni, Yanyan Lan, Zhi-Ming Ma, Wei-Ying Ma:
Fractional Denoising for 3D Molecular Pre-training. CoRR abs/2307.10683 (2023) - [i42]Zicheng Ye, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma:
On the Weight Distribution of Weights Less than 2wmin in Polar Codes. CoRR abs/2308.10024 (2023) - [i41]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 abs/2309.05019 (2023) - [i40]Bowen Gao, Yinjun Jia, Yuanle Mo, Yuyan Ni, Wei-Ying Ma, Zhiming Ma, Yanyan Lan:
Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment. CoRR abs/2310.07229 (2023) - [i39]Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan:
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method. CoRR abs/2311.02124 (2023) - [i38]Yuyan Ni, Yanyan Lan, Ao Liu, Zhiming Ma:
Elastic Information Bottleneck. CoRR abs/2311.03955 (2023) - [i37]Rui Zhang, Qi Meng, Zhi-Ming Ma:
Deciphering and integrating invariants for neural operator learning with various physical mechanisms. CoRR abs/2311.14361 (2023) - [i36]Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhiming Ma, Shengchao Liu:
Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. CoRR abs/2312.03475 (2023) - [i35]Peiyan Hu, Yue Wang, Zhi-Ming Ma:
Better Neural PDE Solvers Through Data-Free Mesh Movers. CoRR abs/2312.05583 (2023) - [i34]Shuai Yuan, Liuquan Yao, Yuan Li, Huazi Zhang, Jun Wang, Wen Tong, Zhiming Ma:
Achieving the Fundamental Limit of Lossless Analog Compression via Polarization. CoRR abs/2312.06200 (2023) - 2022
- [j12]Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma:
Constructing the Basis Path Set by Eliminating the Path Dependency. J. Syst. Sci. Complex. 35(5): 1944-1962 (2022) - [c37]Yuancheng Sun, Yimeng Chen, Weizhi Ma, Wenhao Huang, Kang Liu, Zhiming Ma, Wei-Ying Ma, Yanyan Lan:
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction. CIKM 2022: 3505-3513 - [c36]Dawei Yin, Yuan Li, Xianbin Wang, Jiajie Tong, Huazi Zhang, Jun Wang, Guanghui Wang, Guiying Yan, Zhiming Ma:
On the Message Passing Efficiency of Polar and Low-Density Parity-Check Decoders. GLOBECOM (Workshops) 2022: 528-534 - [c35]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 - [c34]Zicheng Ye, Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma:
The Complete SC-Invariant Affine Automorphisms of Polar Codes. ISIT 2022: 2368-2373 - [c33]Yuan Li, Xianbin Wang, Huazi Zhang, Jun Wang, Wen Tong, Guiying Yan, Zhiming Ma:
Deterministic Identification over Channels without CSI. ITW 2022: 332-337 - [c32]Yimeng Chen, Ruibin Xiong, Zhi-Ming Ma, Yanyan Lan:
When Does Group Invariant Learning Survive Spurious Correlations? NeurIPS 2022 - [c31]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 - [c30]Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma:
Characterization of Excess Risk for Locally Strongly Convex Population Risk. NeurIPS 2022 - [i33]Zicheng Ye, Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma:
The Complete SC-invariant Affine Automorphisms of Polar Codes. CoRR abs/2201.12714 (2022) - [i32]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 abs/2204.06255 (2022) - [i31]Yuan Li, Xianbin Wang, Huazi Zhang, Jun Wang, Wen Tong, Guiying Yan, Zhiming Ma:
Deterministic Identification over Channels without CSI. CoRR abs/2205.06523 (2022) - [i30]Dawei Yin, Yuan Li, Xianbin Wang, Jiajie Tong, Huazi Zhang, Jun Wang, Guanghui Wang, Guiying Yan, Zhiming Ma:
On the Message Passing Efficiency of Polar and Low-Density Parity-Check Decoders. CoRR abs/2206.06897 (2022) - [i29]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 abs/2206.09571 (2022) - [i28]Yimeng Chen, Ruibin Xiong, Zhiming Ma, Yanyan Lan:
When Does Group Invariant Learning Survive Spurious Correlations? CoRR abs/2206.14534 (2022) - [i27]Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma:
Improved OOD Generalization via Conditional Invariant Regularizer. CoRR abs/2207.06687 (2022) - [i26]Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen:
Provable Adaptivity in Adam. CoRR abs/2208.09900 (2022) - [i25]Yuancheng Sun, Yimeng Chen, Weizhi Ma, Wenhao Huang, Kang Liu, Zhiming Ma, Wei-Ying Ma, Yanyan Lan:
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction. CoRR abs/2211.01978 (2022) - 2021
- [j11]Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma:
Interpreting the Basis Path Set in Neural Networks. J. Syst. Sci. Complex. 34(6): 2155-2167 (2021) - [c29]Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Wen Tong, Guiying Yan, Zhiming Ma:
The Complete Affine Automorphism Group of Polar Codes. GLOBECOM 2021: 1-6 - [c28]Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma:
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. ICLR 2021 - [c27]Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma:
Improved OOD Generalization via Adversarial Training and Pretraing. ICML 2021: 11987-11997 - [c26]Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma:
On the Weight Spectrum of Pre-Transformed Polar Codes. ISIT 2021: 1224-1229 - [c25]Ruibin Xiong, Yimeng Chen, Liang Pang, Xueqi Cheng, Zhi-Ming Ma, Yanyan Lan:
Uncertainty Calibration for Ensemble-Based Debiasing Methods. NeurIPS 2021: 13657-13669 - [i24]Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma:
Towards Accelerating Training of Batch Normalization: A Manifold Perspective. CoRR abs/2101.02916 (2021) - [i23]Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
BN-invariant sharpness regularizes the training model to better generalization. CoRR abs/2101.02944 (2021) - [i22]Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma:
On the Weight Spectrum of Pre-Transformed Polar Codes. CoRR abs/2102.12625 (2021) - [i21]Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma:
Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. CoRR abs/2103.08933 (2021) - [i20]Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Wen Tong, Guiying Yan, Zhiming Ma:
The Complete Affine Automorphism Group of Polar Codes. CoRR abs/2103.14215 (2021) - [i19]Zicheng Ye, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma:
Improving the Gilbert-Varshamov Bound by Graph Spectral Method. CoRR abs/2104.01403 (2021) - [i18]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 abs/2105.11144 (2021) - [i17]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 abs/2106.04166 (2021) - [i16]Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma:
Momentum Doesn't Change the Implicit Bias. CoRR abs/2110.03891 (2021) - 2020
- [j10]Yue Wang, Yuting Liu, Zhi-Ming Ma:
The scale-invariant space for attention layer in neural network. Neurocomputing 392: 1-10 (2020) - [j9]Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Target transfer Q-learning and its convergence analysis. Neurocomputing 392: 11-22 (2020) - [c24]Yimeng Chen, Yanyan Lan, Ruibin Xiong, Liang Pang, Zhiming Ma, Xueqi Cheng:
Evaluating Natural Language Generation via Unbalanced Optimal Transport. IJCAI 2020: 3730-3736 - [i15]Linfang Hou, Liang Pang, Xin Hong, Yanyan Lan, Zhiming Ma, Dawei Yin:
Robust Reinforcement Learning with Wasserstein Constraint. CoRR abs/2006.00945 (2020) - [i14]Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Dynamic of Stochastic Gradient Descent with State-Dependent Noise. CoRR abs/2006.13719 (2020) - [i13]Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma:
Constructing Basis Path Set by Eliminating Path Dependency. CoRR abs/2007.00657 (2020) - [i12]Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma:
Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape. CoRR abs/2012.02456 (2020)
2010 – 2019
- 2019
- [j8]Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu:
Convergence analysis of distributed stochastic gradient descent with shuffling. Neurocomputing 337: 46-57 (2019) - [j7]Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu:
OptQuant: Distributed training of neural networks with optimized quantization mechanisms. Neurocomputing 340: 233-244 (2019) - [c23]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 - [c22]Zhiming Ma, Chun Yuan, Yangyang Cheng, Xinrui Zhu:
Image-to-Tree: A Tree-Structured Decoder for Image Captioning. ICME 2019: 1294-1299 - [c21]Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
BN-invariant Sharpness Regularizes the Training Model to Better Generalization. IJCAI 2019: 4164-4170 - [c20]Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin:
Off-policy Learning for Multiple Loggers. KDD 2019: 1184-1193 - [i11]Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Positively Scale-Invariant Flatness of ReLU Neural Networks. CoRR abs/1903.02237 (2019) - [i10]Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin:
Off-policy Learning for Multiple Loggers. CoRR abs/1907.09652 (2019) - [i9]Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma:
Interpreting Basis Path Set in Neural Networks. CoRR abs/1910.09402 (2019) - 2018
- [c19]Pengfei Zhu, Longyin Wen, Dawei Du, Xiao Bian, Haibin Ling, Qinghua Hu, Haotian Wu, Qinqin Nie, Hao Cheng, Chenfeng Liu, Xiaoyu Liu, Wenya Ma, Lianjie Wang, Arne Schumann, Dan Wang, Diego Ortego, Elena Luna, Emmanouil Michail, Erik Bochinski, Feng Ni, Filiz Bunyak, Gege Zhang, Guna Seetharaman, Guorong Li, Hongyang Yu, Ioannis Kompatsiaris, Jianfei Zhao, Jie Gao, José M. Martínez, Juan C. SanMiguel, Kannappan Palaniappan, Konstantinos Avgerinakis, Lars Wilko Sommer, Martin Lauer, Mengkun Liu, Noor M. Al-Shakarji, Oliver Acatay, Panagiotis Giannakeris, Qijie Zhao, Qinghua Ma, Qingming Huang, Stefanos Vrochidis, Thomas Sikora, Tobias Senst, Wei Song, Wei Tian, Wenhua Zhang, Yanyun Zhao, Yidong Bai, Yinan Wu, Yongtao Wang, Yuxuan Li, Zhaoliang Pi, Zhiming Ma:
VisDrone-VDT2018: The Vision Meets Drone Video Detection and Tracking Challenge Results. ECCV Workshops (5) 2018: 496-518 - [c18]Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu:
Differential Equations for Modeling Asynchronous Algorithms. IJCAI 2018: 2220-2226 - [i8]Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu:
Differential Equations for Modeling Asynchronous Algorithms. CoRR abs/1805.02991 (2018) - [i7]Yue Wang, Qi Meng, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu:
Target Transfer Q-Learning and Its Convergence Analysis. CoRR abs/1809.08923 (2018) - [i6]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 abs/1809.08926 (2018) - 2017
- [c17]Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. AAAI 2017: 2329-2335 - [c16]Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Generalization Error Bounds for Optimization Algorithms via Stability. AAAI 2017: 2336-2342 - [c15]Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Gradient Descent with Delay Compensation. ICML 2017: 4120-4129 - [c14]Yue Wang, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu:
Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting. NIPS 2017: 5504-5513 - [i5]Qi Meng, Wei Chen, Yue Wang, Zhiming Ma, Tie-Yan Liu:
Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling. CoRR abs/1709.10432 (2017) - 2016
- [j6]Xumin Ni, Wei Guo, Kai Yuan, Xiong Yang, Zhiming Ma, Shuhua Xu, Shihua Zhang:
A Probabilistic Method for Estimating the Sharing of Identity by Descent for Populations with Migration. IEEE ACM Trans. Comput. Biol. Bioinform. 13(2): 281-290 (2016) - [c13]Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Asynchronous Accelerated Stochastic Gradient Descent. IJCAI 2016: 1853-1859 - [c12]Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu:
A Communication-Efficient Parallel Algorithm for Decision Tree. NIPS 2016: 1271-1279 - [i4]Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning. CoRR abs/1609.08326 (2016) - [i3]Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Generalization Error Bounds for Optimization Algorithms via Stability. CoRR abs/1609.08397 (2016) - [i2]Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. CoRR abs/1609.08435 (2016) - [i1]Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu:
A Communication-Efficient Parallel Algorithm for Decision Tree. CoRR abs/1611.01276 (2016) - 2015
- [c11]Haifang Li, Fei Tian, Wei Chen, Tao Qin, Zhiming Ma, Tie-Yan Liu:
Generalization Analysis for Game-Theoretic Machine Learning. AAAI 2015: 2089-2095 - 2014
- [j5]Ying Wang, Ying Zhou, Linfeng Li, Xian Chen, Yuting Liu, Zhiming Ma, Shuhua Xu:
A New Method for Modeling Coalescent Processes with Recombination. BMC Bioinform. 15: 273 (2014) - 2011
- [j4]Tianqi Zhu, Yucheng Hu, Zhiming Ma, De-Xing Zhang, Tiejun Li, Ziheng Yang:
Efficient simulation under a population genetics model of carcinogenesis. Bioinform. 27(6): 837-843 (2011) - [j3]Bin Gao, Tie-Yan Liu, Yuting Liu, Taifeng Wang, Zhiming Ma, Hang Li:
Page importance computation based on Markov processes. Inf. Retr. 14(5): 488-514 (2011) - 2010
- [j2]Yuting Liu, Tie-Yan Liu, Bin Gao, Zhiming Ma, Hang Li:
A framework to compute page importance based on user behaviors. Inf. Retr. 13(1): 22-45 (2010) - [c10]Yuting Liu, Zhiming Ma:
Comparison of Two Algorithms for Computing Page Importance. AAIM 2010: 1-11 - [c9]Wei Chen, Tie-Yan Liu, Zhiming Ma:
Two-Layer Generalization Analysis for Ranking Using Rademacher Average. NIPS 2010: 370-378
2000 – 2009
- 2009
- [c8]Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Hang Li:
A general markov framework for page importance computation. CIKM 2009: 1835-1838 - [c7]Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li:
Generalization analysis of listwise learning-to-rank algorithms. ICML 2009: 577-584 - [c6]Wei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li:
Ranking Measures and Loss Functions in Learning to Rank. NIPS 2009: 315-323 - 2008
- [c5]Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li:
Query-level stability and generalization in learning to rank. ICML 2008: 512-519 - [c4]Yuting Liu, Bin Gao, Tie-Yan Liu, Ying Zhang, Zhiming Ma, Shuyuan He, Hang Li:
BrowseRank: letting web users vote for page importance. SIGIR 2008: 451-458 - 2007
- [j1]Ying Bao, Guang Feng, Tie-Yan Liu, Zhiming Ma, Ying Wang:
Ranking Websites: A Probabilistic View. Internet Math. 3(3): 295-320 (2007) - [c3]Yuting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li:
Supervised rank aggregation. WWW 2007: 481-490 - 2006
- [c2]Guang Feng, Tie-Yan Liu, Ying Wang, Ying Bao, Zhiming Ma, Xu-Dong Zhang, Wei-Ying Ma:
AggregateRank: bringing order to web sites. SIGIR 2006: 75-82 - 2005
- [c1]Guolie Lan, Zhiming Ma, Su-Yong Sun:
Coverage Problem of Wireless Sensor Networks. CJCDGCGT 2005: 88-100
Coauthor Index
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