Zhanxing Zhu

发表

Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes pdf

Zhanxing Zhu, E Weinan, Lei Wu, 2017, ArXiv.

Stochastic Parallel Block Coordinate Descent for Large-Scale Saddle Point Problems

Zhanxing Zhu, Amos J. Storkey, 2016, AAAI.

On the Noisy Gradient Descent that Generalizes as SGD

Zhanxing Zhu, Vladimir Braverman, Haoyi Xiong, 2019, ICML.

Efficient Neural Architecture Search via Proximal Iterations

Zhanxing Zhu, Quanming Yao, Wei-Wei Tu, 2020, AAAI.

Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy pdf

Zhanxing Zhu, Ke Sun, Zhouchen Lin, 2019, ArXiv.

Virtual Adversarial Training on Graph Convolutional Networks in Node Classification pdf

Zhanxing Zhu, Ke Sun, Zhouchen Lin, 2019, PRCV.

Integrating local information for inference and optimization in machine learning

Zhanxing Zhu, Zhanxing Zhu, 2016 .

Multiplicative Updates for Learning with Stochastic Matrices

Erkki Oja, Zhanxing Zhu, Zhirong Yang, 2013, SCIA.

Reinforced Continual Learning

Zhanxing Zhu, Ju Xu, Zhanxing Zhu, 2018, NeurIPS.

A Guider Network for Multi-Dual Learning

Dongyan Zhao, Zhanxing Zhu, Jinwen Ma, 2018 .

Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks

Zhanxing Zhu, Rafal Mantiuk, Nanyang Ye, 2017, NIPS.

SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction

Zhanxing Zhu, Huizhuo Yuan, Jinzhu Jia, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors pdf

Zhanxing Zhu, Ke Sun, Zhouchen Lin, 2019, ArXiv.

Bayesian Optimized Continual Learning with Attention Mechanism pdf

Zhanxing Zhu, Ju Xu, Jin Ma, 2019, ArXiv.

You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle pdf

Bin Dong, Zhanxing Zhu, Yiping Lu, 2019, NeurIPS.

A Deep Learning-based Framework for Conducting Stealthy Attacks in Industrial Control Systems pdf

Zhanxing Zhu, Tingting Li, Cheng Feng, 2017, ArXiv.

The Multiplicative Noise in Stochastic Gradient Descent: Data-Dependent Regularization, Continuous and Discrete Approximation pdf

Zhanxing Zhu, Haoyi Xiong, Wenqing Hu, 2019, ArXiv.

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence

Zhanxing Zhu, Amos Storkey, 2016, AAAI 2016.

Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix pdf

Dongyan Zhao, Yansong Feng, Zhanxing Zhu, 2017, ACL.

Simplifying Graph Attention Networks with Source-Target Separation

Yansong Feng, Zhanxing Zhu, Rui Yan, 2020, ECAI.

Quasi-potential as an implicit regularizer for the loss function in the stochastic gradient descent pdf

Zhanxing Zhu, Haoyi Xiong, Wenqing Hu, 2019, ArXiv.

Neural Control Variates for Variance Reduction pdf

Zhanxing Zhu, Mingjun Zhong, Ruosi Wan, 2018, ArXiv.

Amata: An Annealing Mechanism for Adversarial Training Acceleration pdf

Zhanxing Zhu, Nanyang Ye, Qianxiao Li, 2019, AAAI.

Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach

Zheng Wang, Yansong Feng, Zhanxing Zhu, 2018, CCS.

3D Graph Convolutional Networks with Temporal Graphs: A Spatial Information Free Framework For Traffic Forecasting pdf

Zhanxing Zhu, Bing Yu, Jiyong Zhang, 2019, ArXiv.

Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework pdf

Qiang Liu, Zhanxing Zhu, Mao Ye, 2020, NeurIPS.

Spatio-Temporal Manifold Learning for Human Motions via Long-Horizon Modeling

Zhanxing Zhu, Hubert P. H. Shum, Edmond S. L. Ho, 2019, IEEE Transactions on Visualization and Computer Graphics.

Tangent-Normal Adversarial Regularization for Semi-Supervised Learning

Zhanxing Zhu, Bing Yu, Jingfeng Wu, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling pdf

Zhanxing Zhu, Bing Yu, Haoteng Yin, 2019, ArXiv.

The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects

Zhanxing Zhu, Jinwen Ma, Bing Yu, 2018, ICML.

Exploring and Enhancing the Transferability of Adversarial Examples

Zhanxing Zhu, Lei Wu, Cheng Tai, 2018 .

Interpreting Adversarially Trained Convolutional Neural Networks

Zhanxing Zhu, Tianyuan Zhang, Zhanxing Zhu, 2019, ICML.

Hyperspectral unmixing using non-negative matrix factorization with automatically estimating regularization parameters

Zhiguo Jiang, Zhanxing Zhu, Zhenwei Shi, 2011, 2011 Seventh International Conference on Natural Computation.

On the Learning Dynamics of Two-layer Nonlinear Convolutional Neural Networks pdf

Zhanxing Zhu, Bing Yu, Junzhao Zhang, 2019, ArXiv.

AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models pdf

Zhanxing Zhu, Ke Sun, Zhouchen Lin, 2019, ICLR.

Understanding and Enhancing the Transferability of Adversarial Examples pdf

Lei Wu, Zhanxing Zhu, E Weinan, 2018, ArXiv.

On Breaking Deep Generative Model-based Defenses and Beyond

Zhanxing Zhu, Renjie Xie, Yanzhi Chen, 2020, ICML.

Neural Approximate Sufficient Statistics for Implicit Models pdf

Zhanxing Zhu, Aaron C. Courville, Aaron Courville, 2020, ICLR.

Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher pdf

Zhanxing Zhu, Guangda Ji, Zhanxing Zhu, 2020, NeurIPS.

You Only Propagate Once: Painless Adversarial Training Using Maximal Principle

Bin Dong, Zhanxing Zhu, Yiping Lu, 2019 .

Bayesian Adversarial Learning

Zhanxing Zhu, Nanyang Ye, Zhanxing Zhu, 2018, NeurIPS.

Differentiable Neural Architecture Search via Proximal Iterations pdf

Zhanxing Zhu, Quanming Yao, Wei-Wei Tu, 2019, ArXiv.

Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data pdf

Zhanxing Zhu, Bing Yu, He Wang, 2020, ArXiv.

Quadratic Form Innovation to Blind Source Separation

Zhiguo Jiang, Zhanxing Zhu, Zhenwei Shi, 2009, 2009 Fifth International Conference on Natural Computation.

A method of automatically estimating the regularization parameter for Non-negative Matrix Factorization

Zhiguo Jiang, Zhanxing Zhu, Zhenwei Shi, 2010, 2010 Sixth International Conference on Natural Computation.

Stochastic Fractional Hamiltonian Monte Carlo

Zhanxing Zhu, Nanyang Ye, Zhanxing Zhu, 2018, IJCAI.

Neural Information Processing Systems (NIPS)

Zhanxing Zhu, Amos Storkey, Benedict Leimkuhler, 2015 .

Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting

Zhanxing Zhu, Bing Yu, Haoteng Yin, 2017, IJCAI.

Aggregation Under Bias: Rényi Divergence Aggregation and Its Implementation via Machine Learning Markets

Zhanxing Zhu, Amos J. Storkey, Jinli Hu, 2015, ECML/PKDD.

Informative Dropout for Robust Representation Learning: A Shape-bias Perspective

Zhanxing Zhu, Yadong Mu, Jingdong Wang, 2020, ICML.

Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems

Zhanxing Zhu, Amos J. Storkey, A. Storkey, 2015, ECML/PKDD.

The Regularization Effects of Anisotropic Noise in Stochastic Gradient Descent pdf

Lei Wu, Zhanxing Zhu, Jinwen Ma, 2018, ArXiv.

SpHMC: Spectral Hamiltonian Monte Carlo

Zhanxing Zhu, Haoyi Xiong, Cheng-Zhong Xu, 2019, AAAI.

Automatic Rank Determination in Projective Nonnegative Matrix Factorization

Erkki Oja, Zhanxing Zhu, Zhirong Yang, 2010, LVA/ICA.

Adversarial attacks on Faster R-CNN object detector

Zhanxing Zhu, Kunfeng Wang, Yutong Wang, 2020, Neurocomputing.

Spherical Motion Dynamics of Deep Neural Networks with Batch Normalization and Weight Decay pdf

Zhanxing Zhu, Jian Sun, Ruosi Wan, 2020, ArXiv.

Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling

Zhanxing Zhu, Benedict J. Leimkuhler, Xiaocheng Shang, 2015, NIPS.

Supervised Distance Preserving Projections

Zhanxing Zhu, Francesco Corona, Timo Similä, 2013, Neural Processing Letters.

Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks

Zhanxing Zhu, Lei Wu, Lei Wu, 2020, ACML.

Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting pdf

Zhanxing Zhu, Mengzhang Li, 2020, ArXiv.

Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN pdf

Zhanxing Zhu, Ke Sun, Zhouchen Lin, 2019, ArXiv.

Global Robustness Verification Networks pdf

Zhanxing Zhu, Meng Sun, Xiyue Zhang, 2020, ArXiv.

Learning to Search Efficient DenseNet with Layer-wise Pruning

Zenglin Xu, Zhanxing Zhu, Xuanyang Zhang, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Functional Bayesian Neural Networks for Model Uncertainty Quantification

Zhanxing Zhu, Nanyang Ye, 2018 .

Multi-Stage Self-Supervised Learning for Graph Convolutional Networks pdf

Zhanxing Zhu, Ke Sun, Zhouchen Lin, 2020, AAAI.

Neural Control Variates for Monte Carlo Variance Reduction

Zhanxing Zhu, Haoyi Xiong, Mingjun Zhong, 2019, ECML/PKDD.

Local Linear Regression for Soft-Sensor Design with Application to an Industrial Deethanizer

Zhanxing Zhu, Amaury Lendasse, Jose A. Romagnoli, 2011 .

Filling the Soap Bubbles: Efficient Black-Box Adversarial Certification with Non-Gaussian Smoothing

Qiang Liu, Zhanxing Zhu, Mao Ye, 2019 .

A Fixed-Point Algorithm for Nonnegative Independent Component Analysis

Zhiguo Jiang, Zhanxing Zhu, Zhenwei Shi, 2009, 2009 Fifth International Conference on Natural Computation.

Langevin Dynamics with Continuous Tempering for High-dimensional Non-convex Optimization pdf

Zhanxing Zhu, Rafal Mantiuk, Nanyang Ye, 2017, ArXiv.

Enhancing the Transferability of Adversarial Examples with Noise Reduced Gradient

Zhanxing Zhu, Lei Wu, Cheng Tai, 2018 .

Towards Making Deep Transfer Learning Never Hurt

Zhanxing Zhu, Haoyi Xiong, Xingjian Li, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Automatic Data Augmentation for 3D Medical Image Segmentation pdf

Zhanxing Zhu, Mengzhang Li, Ju Xu, 2020, MICCAI.

Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning

Jianhong Wang, Zhanxing Zhu, Yaodong Yang, 2017, NeurIPS.

Implicit Regularization Effects of Unbiased Random Label Noises with SGD

Dongrui Wu, Zhanxing Zhu, Dejing Dou, 2021 .

Adversarial Invariant Learning

Zhanxing Zhu, Guang-Zhong Yang, Zhenguo Li, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI pdf

Quanshi Zhang, Zhanxing Zhu, Tian Han, 2021, ArXiv.

Neural Approximate Sufficient Statistics for Implicit Models pdf

Zhanxing Zhu, Aaron Courville, Dinghuai Zhang, 2021, ICLR.

Sampling Sparse Representations with Randomized Measurement Langevin Dynamics

Zhanxing Zhu, Haoyi Xiong, Dejing Dou, 2021, ACM Trans. Knowl. Discov. Data.

Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization pdf

Zhanxing Zhu, Masashi Sugiyama, Zeke Xie, 2021, ICML.

Supervised Distance Preserving Projections: Applications in the quantitative analysis of diesel fuels and light cycle oils from NIR spectra

Zhanxing Zhu, Guilherme A. Barreto, Francesco Corona, 2015 .

Spherical Motion Dynamics of Deep Neural Networks with Batch Normalization and Weight Decay pdf

Zhanxing Zhu, Jian Sun, Ruosi Wan, 2020, ArXiv.

An Annealing Mechanism for Adversarial Training Acceleration

Zhanxing Zhu, Nanyang Ye, Xiao-Yun Zhou, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Supervised Distance Preserving Projection for Dimensionality Reduction

Zhanxing Zhu, Zhanxing Zhu, 2011 .