Zhiming Ma

Orcid: 0000-0003-1169-7627

Affiliations:
  • Academy of Mathematics and Systems Science, Chinese Academy of Sciences


According to our database1, Zhiming Ma authored at least 110 papers between 2005 and 2024.

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Bibliography

2024
On the Distribution of Weights Less Than 2w<sub>min</sub>in Polar Codes.
IEEE Trans. Commun., October, 2024

Affine Automorphism Group of Polar Codes.
IEEE Trans. Inf. Theory, September, 2024

Pre-training with fractional denoising to enhance molecular property prediction.
Nat. Mac. Intell., 2024

Neural networks taking probability distributions as input: A framework for analyzing exchangeable networks.
Neurocomputing, 2024

Erlang Model for Multiple Data Streams (Full Version).
CoRR, 2024

Partial Orders of Sequential Rate-Matched Polar Codes.
CoRR, 2024

On the Weight Spectrum of Rate-Compatible Polar Codes.
CoRR, 2024

A Method to Reduce the Complexity of Computing the Complete Weight Distribution of Polar Codes.
CoRR, 2024

UniGEM: A Unified Approach to Generation and Property Prediction for Molecules.
CoRR, 2024

Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey.
CoRR, 2024

A Generative Approach to Control Complex Physical Systems.
CoRR, 2024

Fundamental Bounds on Unequal Error Protection Codes.
CoRR, 2024

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond.
CoRR, 2024

Entropic Conditional Central Limit Theorem and Hadamard Compression.
CoRR, 2024

Provable Adaptivity of Adam under Non-uniform Smoothness.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

New Partial Orders of Polar Codes for BMSC.
Proceedings of the IEEE International Symposium on Information Theory, 2024

Second-Order Identification Capacity of AWGN Channels.
Proceedings of the IEEE International Symposium on Information Theory, 2024

Neural Jump-Diffusion Temporal Point Processes.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Sliced Denoising: A Physics-Informed Molecular Pre-Training Method.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Better Neural PDE Solvers Through Data-Free Mesh Movers.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
A Weakly Supervised Semantic Segmentation Method Based on Local Superpixel Transformation.
Neural Process. Lett., December, 2023

Incorporating NODE with pre-trained neural differential operator for learning dynamics.
Neurocomputing, April, 2023

Achieving the Fundamental Limit of Lossless Analog Compression via Polarization.
CoRR, 2023

Deciphering and integrating invariants for neural operator learning with various physical mechanisms.
CoRR, 2023

Elastic Information Bottleneck.
CoRR, 2023

On the Weight Distribution of Weights Less than 2w<sub>min</sub> in Polar Codes.
CoRR, 2023

Theoretical Bounds for the Size of Elementary Trapping Sets by Graphic Methods.
CoRR, 2023

Power-law Dynamic arising from machine learning.
CoRR, 2023

Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation.
CoRR, 2023

Improved Finite-Length Bound of Gaussian Unsourced Multiple Access.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2023

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models.
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.
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.
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.
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.
Proceedings of the IEEE International Symposium on Information Theory, 2023

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining.
Proceedings of the International Conference on Machine Learning, 2023

Fractional Denoising for 3D Molecular Pre-training.
Proceedings of the International Conference on Machine Learning, 2023

Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization.
Proceedings of the International Conference on Machine Learning, 2023

Breaking Correlation Shift via Conditional Invariant Regularizer.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Lossless Analog Compression via Polarization.
Proceedings of the IEEE Global Communications Conference, 2023

Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions.
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.
Proceedings of the Artificial Intelligence - Third CAAI International Conference, 2023

Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Constructing the Basis Path Set by Eliminating the Path Dependency.
J. Syst. Sci. Complex., 2022

Provable Adaptivity in Adam.
CoRR, 2022

Improved OOD Generalization via Conditional Invariant Regularizer.
CoRR, 2022

Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations.
CoRR, 2022

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs.
CoRR, 2022

Characterization of Excess Risk for Locally Strongly Convex Population Risk.
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?
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?
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.
Proceedings of the IEEE Information Theory Workshop, 2022

The Complete SC-Invariant Affine Automorphisms of Polar Codes.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Gradient Information Matters in Policy Optimization by Back-propagating through Model.
Proceedings of the Tenth International Conference on Learning Representations, 2022

On the Message Passing Efficiency of Polar and Low-Density Parity-Check Decoders.
Proceedings of the IEEE Globecom 2022 Workshops, 2022

PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Interpreting the Basis Path Set in Neural Networks.
J. Syst. Sci. Complex., 2021

Momentum Doesn't Change the Implicit Bias.
CoRR, 2021

Improved OOD Generalization via Adversarial Training and Pre-training.
CoRR, 2021

Improving the Gilbert-Varshamov Bound by Graph Spectral Method.
CoRR, 2021

Towards Accelerating Training of Batch Normalization: A Manifold Perspective.
CoRR, 2021

Uncertainty Calibration for Ensemble-Based Debiasing Methods.
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.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Improved OOD Generalization via Adversarial Training and Pretraing.
Proceedings of the 38th International Conference on Machine Learning, 2021

Reweighting Augmented Samples by Minimizing the Maximal Expected Loss.
Proceedings of the 9th International Conference on Learning Representations, 2021

The Complete Affine Automorphism Group of Polar Codes.
Proceedings of the IEEE Global Communications Conference, 2021

2020
The scale-invariant space for attention layer in neural network.
Neurocomputing, 2020

Target transfer Q-learning and its convergence analysis.
Neurocomputing, 2020

Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape.
CoRR, 2020

Dynamic of Stochastic Gradient Descent with State-Dependent Noise.
CoRR, 2020

Robust Reinforcement Learning with Wasserstein Constraint.
CoRR, 2020

Evaluating Natural Language Generation via Unbalanced Optimal Transport.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Convergence analysis of distributed stochastic gradient descent with shuffling.
Neurocomputing, 2019

OptQuant: Distributed training of neural networks with optimized quantization mechanisms.
Neurocomputing, 2019

Positively Scale-Invariant Flatness of ReLU Neural Networks.
CoRR, 2019

Off-policy Learning for Multiple Loggers.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

BN-invariant Sharpness Regularizes the Training Model to Better Generalization.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Image-to-Tree: A Tree-Structured Decoder for Image Captioning.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Target Transfer Q-Learning and Its Convergence Analysis.
CoRR, 2018

Differential Equations for Modeling Asynchronous Algorithms.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018


2017
Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting.
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.
Proceedings of the 34th International Conference on Machine Learning, 2017

Generalization Error Bounds for Optimization Algorithms via Stability.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction.
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.
IEEE ACM Trans. Comput. Biol. Bioinform., 2016

Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning.
CoRR, 2016

A Communication-Efficient Parallel Algorithm for Decision Tree.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Asynchronous Accelerated Stochastic Gradient Descent.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
Generalization Analysis for Game-Theoretic Machine Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
A New Method for Modeling Coalescent Processes with Recombination.
BMC Bioinform., 2014

2011
Page importance computation based on Markov processes.
Inf. Retr., 2011

Efficient simulation under a population genetics model of carcinogenesis.
Bioinform., 2011

2010
A framework to compute page importance based on user behaviors.
Inf. Retr., 2010

Two-Layer Generalization Analysis for Ranking Using Rademacher Average.
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.
Proceedings of the Algorithmic Aspects in Information and Management, 2010

2009
Ranking Measures and Loss Functions in Learning to Rank.
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.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

A general markov framework for page importance computation.
Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

2008
BrowseRank: letting web users vote for page importance.
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.
Proceedings of the Machine Learning, 2008

2007
Ranking Websites: A Probabilistic View.
Internet Math., 2007

Supervised rank aggregation.
Proceedings of the 16th International Conference on World Wide Web, 2007

2006
AggregateRank: bringing order to web sites.
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.
Proceedings of the Discrete Geometry, 2005


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