Zhiming Ma

According to our database, Zhiming Ma authored at least 105 papers between 2005 and 2024.

Collaborative distances:

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

2024

On the Distribution of Weights Less Than 2w_minin Polar Codes.

Zicheng Ye, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma

IEEE Trans. Commun., October, 2024

Affine Automorphism Group of Polar Codes.

Zicheng Ye, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma

IEEE Trans. Inf. Theory, September, 2024

Neural networks taking probability distributions as input: A framework for analyzing exchangeable networks.

Chongchong Li, Yuting Liu, Zhi-Ming Ma

Neurocomputing, 2024

Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey.

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

CoRR, 2024

Pre-training with Fractional Denoising to Enhance Molecular Property Prediction.

Yuyan Ni, Shikun Feng, Xin Hong, Yuancheng Sun, Wei-Ying Ma, Zhi-Ming Ma, Qiwei Ye, Yanyan Lan

CoRR, 2024

A Generative Approach to Control Complex Physical Systems.

Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu

CoRR, 2024

Fundamental Bounds on Unequal Error Protection Codes.

Liuquan Yao, Shuai Yuan, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma

CoRR, 2024

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond.

Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen

CoRR, 2024

Entropic Conditional Central Limit Theorem and Hadamard Compression.

Zhi-Ming Ma, Liuquan Yao, Shuai Yuan, Huazi Zhang

CoRR, 2024

Provable Adaptivity of Adam under Non-uniform Smoothness.

Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

New Partial Orders of Polar Codes for BMSC.

Liuquan Yao, Zhichao Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhi-Ming Ma

Proceedings of the IEEE International Symposium on Information Theory, 2024

Second-Order Identification Capacity of AWGN Channels.

Zhicheng Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma

Proceedings of the IEEE International Symposium on Information Theory, 2024

Neural Jump-Diffusion Temporal Point Processes.

Shuai Zhang, Chuan Zhou, Yang Aron Liu, Peng Zhang, Xixun Lin, Zhi-Ming Ma

Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling.

Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion.

Bowen Gao, Minsi Ren, Yuyan Ni, Yanwen Huang, Bo Qiang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning.

Shikun Feng, Yuyan Ni, Minghao Li, Yanwen Huang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Sliced Denoising: A Physics-Informed Molecular Pre-Training Method.

Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Better Neural PDE Solvers Through Data-Free Mesh Movers.

Peiyan Hu, Yue Wang, Zhi-Ming Ma

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment.

Bowen Gao, Yinjun Jia, Yuanle Mo, Yuyan Ni, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A Weakly Supervised Semantic Segmentation Method Based on Local Superpixel Transformation.

Zhiming Ma, Dali Chen, Yilin Mo, Yue Chen, Yumin Zhang

Neural Process. Lett., December, 2023

Incorporating NODE with pre-trained neural differential operator for learning dynamics.

Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhiming Ma, Tie-Yan Liu

Neurocomputing, April, 2023

Achieving the Fundamental Limit of Lossless Analog Compression via Polarization.

Shuai Yuan, Liuquan Yao, Yuan Li, Huazi Zhang, Jun Wang, Wen Tong, Zhiming Ma

CoRR, 2023

Deciphering and integrating invariants for neural operator learning with various physical mechanisms.

Rui Zhang, Qi Meng, Zhi-Ming Ma

CoRR, 2023

Elastic Information Bottleneck.

Yuyan Ni, Yanyan Lan, Ao Liu, Zhiming Ma

CoRR, 2023

On the Weight Distribution of Weights Less than 2w_min in Polar Codes.

Zicheng Ye, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma

CoRR, 2023

Theoretical Bounds for the Size of Elementary Trapping Sets by Graphic Methods.

Haoran Xiong, Zicheng Ye, Huazi Zhang, Jun Wang, Ke Liu, Dawei Yin, Guanghui Wang, Guiying Yan, Zhiming Ma

CoRR, 2023

Power-law Dynamic arising from machine learning.

Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng

CoRR, 2023

Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation.

Rui Zhang, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2023

Improved Finite-Length Bound of Gaussian Unsourced Multiple Access.

Wenxuan Lang, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma

Proceedings of the IEEE Wireless Communications and Networking Conference, 2023

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models.

Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma

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

Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials.

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

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

A new perspective on building efficient and expressive 3D equivariant graph neural networks.

Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma

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

Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion.

Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu

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

On the Weight Spectrum Improvement of Pre-transformed Reed-Muller Codes and Polar Codes.

Yuan Li, Zicheng Ye, Huazi Zhang, Jun Wang, Guiying Yan, Zhiming Ma

Proceedings of the IEEE International Symposium on Information Theory, 2023

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining.

Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang

Proceedings of the International Conference on Machine Learning, 2023

Fractional Denoising for 3D Molecular Pre-training.

Shikun Feng, Yuyan Ni, Yanyan Lan, Zhi-Ming Ma, Wei-Ying Ma

Proceedings of the International Conference on Machine Learning, 2023

Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization.

Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhi-Ming Ma

Proceedings of the International Conference on Machine Learning, 2023

Breaking Correlation Shift via Conditional Invariant Regularizer.

Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Lossless Analog Compression via Polarization.

Shuai Yuan, Liuquan Yao, Yuan Li, Huazi Zhang, Jun Wang, Wen Tong, Zhiming Ma

Proceedings of the IEEE Global Communications Conference, 2023

Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions.

Bohan Wang, Huishuai Zhang, Zhiming Ma, Wei Chen

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

How to Select the Appropriate One from the Trained Models for Model-Based OPE.

Chongchong Li, Yue Wang, Zhi-Ming Ma, Yuting Liu

Proceedings of the Artificial Intelligence - Third CAAI International Conference, 2023

Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations.

Shiqi Gong, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhiming Ma, Hao Ni, Tie-Yan Liu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Constructing the Basis Path Set by Eliminating the Path Dependency.

Juanping Zhu, Qi Meng, Wei Chen, Yue Wang, Zhiming Ma

J. Syst. Sci. Complex., 2022

Provable Adaptivity in Adam.

Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen

CoRR, 2022

Improved OOD Generalization via Conditional Invariant Regularizer.

Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma

CoRR, 2022

Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations.

Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2022

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs.

Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2022

Characterization of Excess Risk for Locally Strongly Convex Population Risk.

Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma

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

Does Momentum Change the Implicit Regularization on Separable Data?

Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

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

When Does Group Invariant Learning Survive Spurious Correlations?

Yimeng Chen, Ruibin Xiong, Zhi-Ming Ma, Yanyan Lan

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

Deterministic Identification over Channels without CSI.

Yuan Li, Xianbin Wang, Huazi Zhang, Jun Wang, Wen Tong, Guiying Yan, Zhiming Ma

Proceedings of the IEEE Information Theory Workshop, 2022

The Complete SC-Invariant Affine Automorphisms of Polar Codes.

Zicheng Ye, Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma

Proceedings of the IEEE International Symposium on Information Theory, 2022

Gradient Information Matters in Policy Optimization by Back-propagating through Model.

Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu

Proceedings of the Tenth International Conference on Learning Representations, 2022

On the Message Passing Efficiency of Polar and Low-Density Parity-Check Decoders.

Dawei Yin, Yuan Li, Xianbin Wang, Jiajie Tong, Huazi Zhang, Jun Wang, Guanghui Wang, Guiying Yan, Zhiming Ma

Proceedings of the IEEE Globecom 2022 Workshops, 2022

PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction.

Yuancheng Sun, Yimeng Chen, Weizhi Ma, Wenhao Huang, Kang Liu, Zhiming Ma, Wei-Ying Ma, Yanyan Lan

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Interpreting the Basis Path Set in Neural Networks.

Juanping Zhu, Qi Meng, Wei Chen, Zhiming Ma

J. Syst. Sci. Complex., 2021

Momentum Doesn't Change the Implicit Bias.

Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma

CoRR, 2021

Improved OOD Generalization via Adversarial Training and Pre-training.

Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma

CoRR, 2021

Improving the Gilbert-Varshamov Bound by Graph Spectral Method.

Zicheng Ye, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma

CoRR, 2021

Towards Accelerating Training of Batch Normalization: A Manifold Perspective.

Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma

CoRR, 2021

Uncertainty Calibration for Ensemble-Based Debiasing Methods.

Ruibin Xiong, Yimeng Chen, Liang Pang, Xueqi Cheng, Zhi-Ming Ma, Yanyan Lan

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

On the Weight Spectrum of Pre-Transformed Polar Codes.

Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Guiying Yan, Zhiming Ma

Proceedings of the IEEE International Symposium on Information Theory, 2021

Improved OOD Generalization via Adversarial Training and Pretraing.

Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma

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

Reweighting Augmented Samples by Minimizing the Maximal Expected Loss.

Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma

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

The Complete Affine Automorphism Group of Polar Codes.

Yuan Li, Huazi Zhang, Rong Li, Jun Wang, Wen Tong, Guiying Yan, Zhiming Ma

Proceedings of the IEEE Global Communications Conference, 2021

2020

The scale-invariant space for attention layer in neural network.

Yue Wang, Yuting Liu, Zhi-Ming Ma

Neurocomputing, 2020

Target transfer Q-learning and its convergence analysis.

Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Neurocomputing, 2020

Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape.

Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma

CoRR, 2020

Dynamic of Stochastic Gradient Descent with State-Dependent Noise.

Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2020

Robust Reinforcement Learning with Wasserstein Constraint.

Linfang Hou, Liang Pang, Xin Hong, Yanyan Lan, Zhiming Ma, Dawei Yin

CoRR, 2020

Evaluating Natural Language Generation via Unbalanced Optimal Transport.

Yimeng Chen, Yanyan Lan, Ruibin Xiong, Liang Pang, Zhiming Ma, Xueqi Cheng

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Convergence analysis of distributed stochastic gradient descent with shuffling.

Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu

Neurocomputing, 2019

OptQuant: Distributed training of neural networks with optimized quantization mechanisms.

Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu

Neurocomputing, 2019

Positively Scale-Invariant Flatness of ReLU Neural Networks.

Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

CoRR, 2019

Off-policy Learning for Multiple Loggers.

Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

BN-invariant Sharpness Regularizes the Training Model to Better Generalization.

Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Image-to-Tree: A Tree-Structured Decoder for Image Captioning.

Zhiming Ma, Chun Yuan, Yangyang Cheng, Xinrui Zhu

Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space.

Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Target Transfer Q-Learning and Its Convergence Analysis.

Yue Wang, Qi Meng, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu

CoRR, 2018

Differential Equations for Modeling Asynchronous Algorithms.

Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

VisDrone-VDT2018: The Vision Meets Drone Video Detection and Tracking Challenge Results.

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

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017

Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting.

Yue Wang, Wei Chen, Yuting Liu, Zhiming Ma, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Asynchronous Stochastic Gradient Descent with Delay Compensation.

Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu

Proceedings of the 34th International Conference on Machine Learning, 2017

Generalization Error Bounds for Optimization Algorithms via Stability.

Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction.

Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

A Probabilistic Method for Estimating the Sharing of Identity by Descent for Populations with Migration.

Xumin Ni, Wei Guo, Kai Yuan, Xiong Yang, Zhiming Ma, Shuhua Xu, Shihua Zhang

IEEE ACM Trans. Comput. Biol. Bioinform., 2016

Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning.

Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu

CoRR, 2016

A Communication-Efficient Parallel Algorithm for Decision Tree.

Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Asynchronous Accelerated Stochastic Gradient Descent.

Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Generalization Analysis for Game-Theoretic Machine Learning.

Haifang Li, Fei Tian, Wei Chen, Tao Qin, Zhiming Ma, Tie-Yan Liu

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

A New Method for Modeling Coalescent Processes with Recombination.

Ying Wang, Ying Zhou, Linfeng Li, Xian Chen, Yuting Liu, Zhiming Ma, Shuhua Xu

BMC Bioinform., 2014

2011

Page importance computation based on Markov processes.

Bin Gao, Tie-Yan Liu, Yuting Liu, Taifeng Wang, Zhiming Ma, Hang Li

Inf. Retr., 2011

Efficient simulation under a population genetics model of carcinogenesis.

Tianqi Zhu, Yucheng Hu, Zhiming Ma, De-Xing Zhang, Tiejun Li, Ziheng Yang

Bioinform., 2011

2010

A framework to compute page importance based on user behaviors.

Yuting Liu, Tie-Yan Liu, Bin Gao, Zhiming Ma, Hang Li

Inf. Retr., 2010

Two-Layer Generalization Analysis for Ranking Using Rademacher Average.

Wei Chen, Tie-Yan Liu, Zhiming Ma

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Comparison of Two Algorithms for Computing Page Importance.

Yuting Liu, Zhiming Ma

Proceedings of the Algorithmic Aspects in Information and Management, 2010

2009

Ranking Measures and Loss Functions in Learning to Rank.

Wei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Generalization analysis of listwise learning-to-rank algorithms.

Yanyan Lan, Tie-Yan Liu, Zhiming Ma, Hang Li

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

A general markov framework for page importance computation.

Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Hang Li

Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

2008

BrowseRank: letting web users vote for page importance.

Yuting Liu, Bin Gao, Tie-Yan Liu, Ying Zhang, Zhiming Ma, Shuyuan He, Hang Li

Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2008

Query-level stability and generalization in learning to rank.

Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li

Proceedings of the Machine Learning, 2008

2007

Ranking Websites: A Probabilistic View.

Ying Bao, Guang Feng, Tie-Yan Liu, Zhiming Ma, Ying Wang

Internet Math., 2007

Supervised rank aggregation.

Yuting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li

Proceedings of the 16th International Conference on World Wide Web, 2007

2006

AggregateRank: bringing order to web sites.

Guang Feng, Tie-Yan Liu, Ying Wang, Ying Bao, Zhiming Ma, Xu-Dong Zhang, Wei-Ying Ma

Proceedings of the SIGIR 2006: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2006

2005

Coverage Problem of Wireless Sensor Networks.

Guolie Lan, Zhiming Ma, Su-Yong Sun

Proceedings of the Discrete Geometry, 2005