publications

publications by categories in reversed chronological order.

2023

  1. ICML
    MonoFlow: Rethinking Divergence GANs via the Perspective of Differential Equations
    Mingxuan Yi ,  Zhanxing Zhu ,  and  Song Liu
    In International Conference for Machine Learning (ICML) , 2023
    PDF
  2. NeurIPS
    Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling
    Ting Li ,  Jianguo Li ,  and  Zhanxing Zhu
    In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS) , 2023
    PDF
  3. NeurIPS
    Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
    Bochen Lyu ,  and  Zhanxing Zhu
    In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS) , 2023
    PDF
  4. MLST
    Stochastic Gradient Descent with Random Label Noises: Doubly Stochastic Models and Inference Stabilizer
    Haoyi Xiong ,  Xuhong Li ,  Boyang Yu ,  Dongrui Wu ,  Zhanxing Zhu ,  and  Dejing Dou
    Machine Learning: Science and Technology, 2023

2022

  1. ICLR
    Fine-grained differentiable physics: a yarn-level model for fabrics
    Deshan Gong ,  Zhanxing Zhu ,  Andrew J Bulpitt ,  and  He Wang
    In International Conference on Learning Representation , 2022
  2. ICLR
    Implicit Bias of Adversarial Training for Deep Neural Networks
    Bochen Lv ,  and  Zhanxing Zhu
    In International Conference on Learning Representation , 2022
    PDF
  3. TKDD
    Grod: Deep learning with gradients orthogonal decomposition for knowledge transfer, distillation, and adversarial training
    Haoyi Xiong ,  Ruosi Wan ,  Jian Zhao ,  Zeyu Chen ,  Xingjian Li ,  Zhanxing Zhu , and 1 more author
    ACM Transactions on Knowledge Discovery from Data, 2022

2021

  1. TVCG
    Spatio-Temporal Manifold Learning for Human Motions via Long-Horizon Modeling
    He Wang ,  Edmond S. L. Ho ,  Hubert P. H. Shum ,  and  Zhanxing Zhu
    IEEE Transactions on Visualization and Computer Graphics, 2021
  2. TKDD
    Sampling sparse representations with randomized measurement langevin dynamics
    Kafeng Wang ,  Haoyi Xiong ,  Jiang Bian ,  Zhanxing Zhu ,  Qian Gao ,  Zhishan Guo , and 3 more authors
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2021
  3. ICML
    Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
    Zeke Xie ,  Li Yuan ,  Zhanxing Zhu ,  and  Masashi Sugiyama
    In International Conference for Machine Learning (ICML) , 2021
  4. ICLR
    AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
    Ke Sun ,  Zhanxing Zhu ,  and  Zhouchen Lin
    In International Conference on Learning Representation , 2021
  5. CVPR
    Adversarial invariant learning
    Nanyang Ye ,  Jingxuan Tang ,  Huayu Deng ,  Xiao-Yun Zhou ,  Qianxiao Li ,  Zhenguo Li , and 2 more authors
    In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2021
  6. TPAMI
    Adaptive progressive continual learning
    Ju Xu ,  Jin Ma ,  Xuesong Gao ,  and  Zhanxing Zhu
    IEEE transactions on pattern analysis and machine intelligence, 2021
  7. TNNLS
    An annealing mechanism for adversarial training acceleration
    Nanyang Ye ,  Qianxiao Li ,  Xiao-Yun Zhou ,  and  Zhanxing Zhu
    IEEE Transactions on Neural Networks and Learning Systems, 2021
  8. NeurIPS
    Spherical motion dynamics: Learning dynamics of normalized neural network using sgd and weight decay
    Ruosi Wan ,  Zhanxing Zhu ,  Xiangyu Zhang ,  and  Jian Sun
    Advances in Neural Information Processing Systems (NeurIPS), 2021
    PDF

2020

  1. IJCNN
    Learning to search efficient densenet with layer-wise pruning
    Xuanyang Zhang ,  Hao Liu ,  Zhanxing Zhu ,  and  Zenglin Xu
    In 2020 International Joint Conference on Neural Networks (IJCNN) , 2020
  2. ECML
    Neural control variates for Monte Carlo variance reduction
    Ruosi Wan ,  Mingjun Zhong ,  Haoyi Xiong ,  and  Zhanxing Zhu
    In Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part II , 2020
  3. AAAI
    Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes.
    Ke Sun ,  Zhouchen Lin ,  and  Zhanxing Zhu
    In AAAI 2020 , 2020
  4. AAAI
    Efficient Neural Architecture Search via Proximal Iterations.
    Quanming Yao ,  Ju Xu ,  Wei-Wei Tu ,  and  Zhanxing Zhu
    In AAAI 2020 , 2020
  5. TOPS
    Using generative adversarial networks to break and protect text captchas
    Guixin Ye ,  Zhanyong Tang ,  Dingyi Fang ,  Zhanxing Zhu ,  Yansong Feng ,  Pengfei Xu , and 3 more authors
    ACM Transactions on Privacy and Security (TOPS), 2020
  6. ICML
    On the Noisy Gradient Descent that Generalizes as SGD
    Jingfeng Wu ,  Wenqing Hu ,  Haoyi Xiong ,  Jun Huan ,  Vladimir Braverman ,  and  Zhanxing Zhu
    In International Conference for Machine Learning (ICML 2020) , 2020
  7. AAAI
    Amata: An Annealing Mechanism for Adversarial Training Acceleration
    Nanyang Ye ,  Qianxiao Li ,  Xiao-Yun Zhou ,  and  Zhanxing Zhu
    In AAAI , 2020
  8. ECAI
    Simplifying Graph Attention Networks with Source-Target Separation
    Hantao Guo ,  Rui Yan ,  Yansong Feng ,  Xuesong Gao ,  and  Zhanxing Zhu
    In ECAI , 2020
  9. NeurIPS
    Black-box certification with randomized smoothing: A functional optimization based framework
    Dinghuai Zhang ,  Mao Ye ,  Chengyue Gong ,  Zhanxing Zhu ,  and  Qiang Liu
    In NeurIPS , 2020
  10. ICML
    Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
    Baifeng Shi ,  Dinghuai Zhang ,  Qi Dai ,  Zhanxing Zhu ,  Yadong Mu ,  and  Jingdong Wang
    In International Conference for Machine Learning (ICML) , 2020
  11. MICCAI
    Automatic data augmentation for 3D medical image segmentation
    Ju Xu ,  Mengzhang Li ,  and  Zhanxing Zhu
    In Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part I 23 , 2020
  12. ACML
    Towards understanding and improving the transferability of adversarial examples in deep neural networks
    Lei Wu ,  and  Zhanxing Zhu
    In Asian Conference on Machine Learning , 2020
  13. ICLR
    Neural Approximate Sufficient Statistics for Implicit Models
    Yanzhi Chen ,  Dinghuai Zhang ,  Michael Gutmann ,  Aaron Courville ,  and  Zhanxing Zhu
    In International Conference on Learning Representation , 2020
  14. NeurIPS
    Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
    Guangda Ji ,  and  Zhanxing Zhu
    In Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) , 2020
    PDF
  15. ICML
    On breaking deep generative model-based defenses and beyond
    Yanzhi Chen ,  Renjie Xie ,  and  Zhanxing Zhu
    In International Conference on Machine Learning , 2020
  16. AAAI
    Spatial-temporal fusion graph neural networks for traffic flow forecasting
    Mengzhang Li ,  and  Zhanxing Zhu
    In AAAI Conference on Artificial Intelligence , 2020

2019

  1. AAAI
    SpHMC: Spectral Hamiltonian Monte Carlo
    Haoyi Xiong ,  Kafeng Wang ,  Jiang Bian ,  Zhanxing Zhu ,  Cheng-Zhong Xu ,  Zhishan Guo , and 1 more author
    In AAAI 2019 , 2019
  2. Lancet
    Novel subgroups of patients with adult-onset diabetes in Chinese and US populations
    Xiantong Zou ,  Xianghai Zhou ,  Zhanxing Zhu ,  and  Linong Ji
    The Lancet Diabetes & Endocrinology, 2019
  3. PRCV
    Virtual adversarial training on graph convolutional networks in node classification
    Ke Sun ,  Zhouchen Lin ,  Hantao Guo ,  and  Zhanxing Zhu
    In Pattern Recognition and Computer Vision: Second Chinese Conference, PRCV 2019, Xi’an, China, November 8–11, 2019, Proceedings, Part I 2 , 2019
  4. 3D graph convolutional networks with temporal graphs: A spatial information free framework for traffic forecasting
    Bing Yu ,  Mengzhang Li ,  Jiyong Zhang ,  and  Zhanxing Zhu
    arXiv preprint arXiv:1903.00919, 2019
  5. ST-UNet: A spatio-temporal U-network for graph-structured time series modeling
    Bing Yu ,  Haoteng Yin ,  and  Zhanxing Zhu
    arXiv preprint arXiv:1903.05631, 2019
  6. NeurIPS
    You only propagate once: Accelerating adversarial training via maximal principle
    Dinghuai Zhang ,  Tianyuan Zhang ,  Yiping Lu ,  Zhanxing Zhu ,  and  Bin Dong
    In Advances in Neural Information Processing Systems, 2019 , 2019
    PDF
  7. ICML
    Interpreting Adversarially Trained Convolutional Neural Networks
    Tianyuan Zhang ,  and  Zhanxing Zhu
    In International Conference on Machine Learning (ICML 2019) , 2019
  8. ICML
    The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
    Zhanxing Zhu ,  Jingfeng Wu ,  Bing Yu ,  Lei Wu ,  and  Jinwen Ma
    In International Conference on Machine Learning (ICML 2019) , 2019
  9. NLPCC
    How question generation can help question answering over knowledge base
    Sen Hu ,  Lei Zou ,  and  Zhanxing Zhu
    In Natural Language Processing and Chinese Computing: 8th CCF International Conference, NLPCC 2019, Dunhuang, China, October 9–14, 2019, Proceedings, Part I 8 , 2019
  10. ICDM
    Towards making deep transfer learning never hurt
    Ruosi Wan ,  Haoyi Xiong ,  Xingjian Li ,  Zhanxing Zhu ,  and  Jun Huan
    In 2019 IEEE International Conference on Data Mining (ICDM) , 2019

2018

  1. IJCAI
    Spatio-temporal graph convolutional neural network: A deep learning framework for traffic forecasting
    Bing Yu ,  Haoteng Yin ,  and  Zhanxing Zhu
    In International Joint Conference of Artificial Intelligence (IJCAI) , 2018
    PDF
  2. NIPS
    Reinforced continual learning
    Ju Xu ,  and  Zhanxing Zhu
    In Advances in Neural Information Processing Systems (NeurIPS 2018) , 2018
  3. CVPR
    Tangent-Normal Adversarial Regularization for Semi-supervised Learning
    Bing Yu ,  Jingfeng Wu ,  and  Zhanxing Zhu
    In CVPR 2019 , 2018
  4. CCS
    Yet another text captcha solver: A generative adversarial network based approach
    Guixin Ye ,  Zhanyong Tang ,  Dingyi Fang ,  Zhanxing Zhu ,  Yansong Feng ,  Pengfei Xu , and 2 more authors
    In Proceedings of the 2018 ACM SIGSAC conference on computer and communications security , 2018
  5. ISBI
    SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction
    Huizhuo Yuan ,  Jinzhu Jia ,  and  Zhanxing Zhu
    In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) , 2018
  6. IJCAI
    Stochastic Fractional Hamiltonian Monte Carlo.
    Nanyang Ye ,  and  Zhanxing Zhu
    In IJCAI , 2018
  7. NIPS
    Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
    Rui Luo ,  Jianhong Wang ,  Yaodong Yang ,  Jun Wang ,  and  Zhanxing Zhu
    Advances in Neural Information Processing Systems, 2018
  8. NIPS
    Bayesian adversarial learning
    Nanyang Ye ,  and  Zhanxing Zhu
    Advances in Neural Information Processing Systems, 2018

2017

  1. ICML
    Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes
    Lei Wu ,  and  Zhanxing Zhu
    In The 34th International Conference on Machine Learning (ICML 2017): Theoretical Machine Learning Workshop , 2017
  2. NIPS
    Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
    Nanyang Ye ,  Zhanxing Zhu ,  and  Rafal K Mantiuk
    In 31st Neural Information Processing Systems (NIPS 2017) , 2017
  3. ACL
    Learning with noise: Enhance distantly supervised relation extraction with dynamic transition matrix
    Bingfeng Luo ,  Yansong Feng ,  Zheng Wang ,  Zhanxing Zhu ,  Songfang Huang ,  Rui Yan , and 1 more author
    In ACL 2017 , 2017

2016

  1. AAAI
    Stochastic parallel block coordinate descent for large-scale saddle point problems
    Zhanxing Zhu ,  and  Amos Storkey
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2016

2015

  1. ECML
    Adaptive stochastic primal-dual coordinate descent for separable saddle point problems
    Zhanxing Zhu ,  and  Amos J Storkey
    In Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I 15 , 2015
  2. ECML
    Aggregation under bias: Rényi divergence aggregation and its implementation via machine learning markets
    Amos J Storkey ,  Zhanxing Zhu ,  and  Jinli Hu
    In Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I 15 , 2015
  3. NIPS
    Covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling
    Xiaocheng Shang ,  Zhanxing Zhu ,  Benedict Leimkuhler ,  and  Amos J Storkey
    In NIPS 2015 , 2015

2013

  1. NPL
    Supervised distance preserving projections
    Zhanxing Zhu ,  Timo Similä ,  and  Francesco Corona
    Neural processing letters, 2013
  2. Multiplicative updates for learning with stochastic matrices
    Zhanxing Zhu ,  Zhirong Yang ,  and  Erkki Oja
    In Image Analysis: 18th Scandinavian Conference, SCIA 2013, Espoo, Finland, June 17-20, 2013. Proceedings 18 , 2013

2011

  1. IFAC
    Local linear regression for soft-sensor design with application to an industrial deethanizer
    Zhanxing Zhu ,  Francesco Corona ,  Amaury Lendasse ,  Roberto Baratti ,  and  Jose A Romagnoli
    IFAC Proceedings Volumes, 2011

2010

  1. Automatic rank determination in projective nonnegative matrix factorization
    Zhirong Yang ,  Zhanxing Zhu ,  and  Erkki Oja
    In International Conference on Latent Variable Analysis and Signal Separation , 2010