Zhanxing Zhu - RankMe

134 papers A* 39A 1B 1C 2Misc 2Journal 69Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Diffusion-based Kriging Model with Graph-enhanced Attention. WWW Mingtao Zhang, Guoli Yang, Zhanxing Zhu, Guangyin Jin, Mengzhu Wang, Xiaoying Bai
2026	—	`conf`	FilDeep: Learning Large Deformations of Elastic-Plastic Solids with Multi-Fidelity Data. KDD (1) Jianheng Tang, Shilong Tao, Zhe Feng, Haonan Sun, Menglu Wang, Zhanxing Zhu, Yunhuai Liu
2026	J	`jnl`	FilDeep: Learning Large Deformations of Elastic-Plastic Solids with Multi-Fidelity Data. CoRR Jianheng Tang, Shilong Tao, Zhe Feng, Haonan Sun, Menglu Wang, Zhanxing Zhu, Yunhuai Liu
2026	J	`jnl`	Neural Latent Arbitrary Lagrangian-Eulerian Grids for Fluid-Solid Interaction. CoRR Shilong Tao, Zhe Feng, Shaohan Chen, Weichen Zhang, Zhanxing Zhu, Yunhuai Liu
2026	A*	`conf`	ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction. AAAI Ruochen Li, Zhanxing Zhu, Tanqiu Qiao, Hubert P. H. Shum
2025	A*	`conf`	A Solvable Attention for Neural Scaling Laws. ICLR Bochen Lyu, Di Wang, Zhanxing Zhu
2025	J	`jnl`	ACU: Analytic Continual Unlearning for Efficient and Exact Forgetting with Privacy Preservation. CoRR Jianheng Tang, Huiping Zhuang, Di Fang, Jiaxu Li, Feijiang Han, Yajiang Huang, Kejia Fan, Leye Wang, Zhanxing Zhu, Shanghang Zhang, Houbing Herbert Song, Yunhuai Liu
2025	J	`jnl`	AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data. CoRR Jianheng Tang, Huiping Zhuang, Jingyu He, Run He, Jingchao Wang, Kejia Fan, Anfeng Liu, Tian Wang, Leye Wang, Zhanxing Zhu, Shanghang Zhang, Houbing Herbert Song, Yunhuai Liu
2025	J	`jnl`	Analyzing the Implicit Bias of Adversarial Training From a Generalized Margin Perspective. IEEE Trans. Pattern Anal. Mach. Intell. Bochen Lyu, Zhanxing Zhu
2025	—	`conf`	D ICANN (1) Zhenyu Liu, Huizhi Liang, Rajiv Ranjan, Zhanxing Zhu, Václav Snásel, Varun Ojha
2025	J	`jnl`	D2R: dual regularization loss with collaborative adversarial generation for model robustness. CoRR Zhenyu Liu, Huizhi Liang, Rajiv Ranjan, Zhanxing Zhu, Václav Snásel, Varun Ojha
2025	A*	`conf`	DyCAST: Learning Dynamic Causal Structure from Time Series. ICLR Yue Cheng, Bochen Lyu, Weiwei Xing, Zhanxing Zhu
2025	A*	`conf`	Effects of Momentum in Implicit Bias of Gradient Flow for Diagonal Linear Networks. AAAI Bochen Lyu, He Wang, Zheng Wang, Zhanxing Zhu
2025	J	`jnl`	Efficient Linear Attention for Multivariate Time Series Modeling via Entropy Equality. CoRR Mingtao Zhang, Guoli Yang, Zhanxing Zhu, Mengzhu Wang, Xiaoying Bai
2025	J	`jnl`	Heavy-Ball Momentum Method in Continuous Time and Discretization Error Analysis. CoRR Bochen Lyu, Xiaojing Zhang, Fangyi Zheng, He Wang, Zheng Wang, Zhanxing Zhu
2025	—	`conf`	LaDEEP: A Deep Learning-based Surrogate Model for Large Deformation of Elastic-Plastic Solids. KDD (2) Shilong Tao, Zhe Feng, Haonan Sun, Zhanxing Zhu, Yunhuai Liu
2025	J	`jnl`	LaDEEP: A Deep Learning-based Surrogate Model for Large Deformation of Elastic-Plastic Solids. CoRR Shilong Tao, Zhe Feng, Haonan Sun, Zhanxing Zhu, Yunhuai Liu
2025	—	`conf`	On Leveraging Unlabeled Data for Concurrent Positive-Unlabeled Classification and Robust Generation. ICIG (2) Bing Yu, Ke Sun, He Wang, Zhouchen Lin, Zhanxing Zhu
2025	J	`jnl`	Transformers with RL or SFT Provably Learn Sparse Boolean Functions, But Differently. CoRR Bochen Lyu, Yiyang Jia, Xiaohao Cai, Zhanxing Zhu
2025	J	`jnl`	Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction. CoRR Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis, Zhanxing Zhu, Hubert P. H. Shum
2025	J	`jnl`	Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction. IEEE Trans. Circuits Syst. Video Technol. Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis, Zhanxing Zhu, Hubert P. H. Shum
2025	A*	`conf`	Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems. ICML Shilong Tao, Zhe Feng, Haonan Sun, Zhanxing Zhu, Yunhuai Liu
2025	J	`jnl`	Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems. CoRR Shilong Tao, Zhe Feng, Haonan Sun, Zhanxing Zhu, Yunhuai Liu
2025	J	`jnl`	ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction. CoRR Ruochen Li, Zhanxing Zhu, Tanqiu Qiao, Hubert P. H. Shum
2024	J	`jnl`	Functional Relation Field: A Model-Agnostic Framework for Multivariate Time Series Forecasting. Artif. Intell. Ting Li, Bing Yu, Jianguo Li, Zhanxing Zhu
2024	A*	`conf`	Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization. NeurIPS Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang, Yang Zhang, Jonathan Scarlett, Zhanxing Zhu, Kenji Kawaguchi
2024	J	`jnl`	Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization. CoRR Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang, Yang Zhang, Jonathan Scarlett, Zhanxing Zhu, Kenji Kawaguchi
2024	J	`jnl`	Stochastic gradient descent with random label noises: doubly stochastic models and inference stabilizer. Mach. Learn. Sci. Technol. Haoyi Xiong, Xuhong Li, Boyang Yu, Dongrui Wu, Zhanxing Zhu, Dejing Dou
2023	J	`jnl`	An Annealing Mechanism for Adversarial Training Acceleration. IEEE Trans. Neural Networks Learn. Syst. Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu
2023	J	`jnl`	Doubly Stochastic Models: Learning with Unbiased Label Noises and Inference Stability. CoRR Haoyi Xiong, Xuhong Li, Boyang Yu, Zhanxing Zhu, Dongrui Wu, Dejing Dou
2023	A*	`conf`	Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network. NeurIPS Bochen Lyu, Zhanxing Zhu
2023	—	`book`	Introduction to Data Science Gaoyan Ou, Zhanxing Zhu, Bin Dong, Weinan E, Binyang Li, Shumin Shi
2023	J	`jnl`	MonoFlow: Rethinking Divergence GANs via the Perspective of Differential Equations. CoRR Mingxuan Yi, Zhanxing Zhu, Song Liu
2023	A*	`conf`	MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows. ICML Mingxuan Yi, Zhanxing Zhu, Song Liu
2023	A*	`conf`	Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling. NeurIPS Ting Li, Jianguo Li, Zhanxing Zhu
2023	C	`conf`	Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy. ACML Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu
2022	J	`jnl`	Adaptive Progressive Continual Learning. IEEE Trans. Pattern Anal. Mach. Intell. Ju Xu, Jin Ma, Xuesong Gao, Zhanxing Zhu
2022	A*	`conf`	Fine-grained Differentiable Physics: A Yarn-level Model for Fabrics. ICLR Deshan Gong, Zhanxing Zhu, Andrew J. Bulpitt, He Wang
2022	J	`jnl`	Fine-grained differentiable physics: a yarn-level model for fabrics. CoRR Deshan Gong, Zhanxing Zhu, Andrew J. Bulpitt, He Wang
2022	J	`jnl`	GrOD: Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training. ACM Trans. Knowl. Discov. Data Haoyi Xiong, Ruosi Wan, Jian Zhao, Zeyu Chen, Xingjian Li, Zhanxing Zhu, Jun Huan
2022	A*	`conf`	Implicit Bias of Adversarial Training for Deep Neural Networks. ICLR Bochen Lv, Zhanxing Zhu
2021	A*	`conf`	AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. ICLR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2021	A*	`conf`	Adversarial Invariant Learning. CVPR Nanyang Ye, Jingxuan Tang, Huayu Deng, Xiao-Yun Zhou, Qianxiao Li, Zhenguo Li, Guang-Zhong Yang, Zhanxing Zhu
2021	A*	`conf`	Amata: An Annealing Mechanism for Adversarial Training Acceleration. AAAI Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu
2021	A*	`conf`	Neural Approximate Sufficient Statistics for Implicit Models. ICLR Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu
2021	A*	`conf`	Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization. ICML Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
2021	J	`jnl`	Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization. CoRR Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
2021	J	`jnl`	Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI. CoRR Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang
2021	J	`jnl`	Sampling Sparse Representations with Randomized Measurement Langevin Dynamics. ACM Trans. Knowl. Discov. Data Kafeng Wang, Haoyi Xiong, Jiang Bian, Zhanxing Zhu, Qian Gao, Zhishan Guo, Cheng-Zhong Xu, Jun Huan, Dejing Dou
2021	A*	`conf`	Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting. AAAI Mengzhang Li, Zhanxing Zhu
2021	J	`jnl`	Spatio-Temporal Manifold Learning for Human Motions via Long-Horizon Modeling. IEEE Trans. Vis. Comput. Graph. He Wang, Edmond S. L. Ho, Hubert P. H. Shum, Zhanxing Zhu
2021	A*	`conf`	Spherical Motion Dynamics: Learning Dynamics of Normalized Neural Network using SGD and Weight Decay. NeurIPS Ruosi Wan, Zhanxing Zhu, Xiangyu Zhang, Jian Sun
2020	J	`jnl`	Adversarial attacks on Faster R-CNN object detector. Neurocomputing Yutong Wang, Kunfeng Wang, Zhanxing Zhu, Feiyue Wang
2020	J	`jnl`	Amata: An Annealing Mechanism for Adversarial Training Acceleration. CoRR Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu
2020	—	`conf`	Automatic Data Augmentation for 3D Medical Image Segmentation. MICCAI (1) Ju Xu, Mengzhang Li, Zhanxing Zhu
2020	J	`jnl`	Automatic Data Augmentation for 3D Medical Image Segmentation. CoRR Ju Xu, Mengzhang Li, Zhanxing Zhu
2020	A*	`conf`	Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. NeurIPS Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu
2020	J	`jnl`	Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. CoRR Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu
2020	J	`jnl`	Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data. CoRR Bing Yu, Ke Sun, He Wang, Zhouchen Lin, Zhanxing Zhu
2020	A*	`conf`	Efficient Neural Architecture Search via Proximal Iterations. AAAI Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu
2020	J	`jnl`	Global Robustness Verification Networks. CoRR Weidi Sun, Yuteng Lu, Xiyue Zhang, Zhanxing Zhu, Meng Sun
2020	A*	`conf`	Informative Dropout for Robust Representation Learning: A Shape-bias Perspective. ICML Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang
2020	J	`jnl`	Informative Dropout for Robust Representation Learning: A Shape-bias Perspective. CoRR Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang
2020	A*	`conf`	Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher. NeurIPS Guangda Ji, Zhanxing Zhu
2020	J	`jnl`	Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher. CoRR Guangda Ji, Zhanxing Zhu
2020	B	`conf`	Learning to Search Efficient DenseNet with Layer-wise Pruning. IJCNN Xuanyang Zhang, Hao Liu, Zhanxing Zhu, Zenglin Xu
2020	A*	`conf`	Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes. AAAI Ke Sun, Zhouchen Lin, Zhanxing Zhu
2020	J	`jnl`	Neural Approximate Sufficient Statistics for Implicit Models. CoRR Yanzhi Chen, Dinghuai Zhang, Michael U. Gutmann, Aaron C. Courville, Zhanxing Zhu
2020	A*	`conf`	On Breaking Deep Generative Model-based Defenses and Beyond. ICML Yanzhi Chen, Renjie Xie, Zhanxing Zhu
2020	A*	`conf`	On the Noisy Gradient Descent that Generalizes as SGD. ICML Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu
2020	A	`conf`	Simplifying Graph Attention Networks with Source-Target Separation. ECAI Hantao Guo, Rui Yan, Yansong Feng, Xuesong Gao, Zhanxing Zhu
2020	J	`jnl`	Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting. CoRR Mengzhang Li, Zhanxing Zhu
2020	J	`jnl`	Spherical Motion Dynamics of Deep Neural Networks with Batch Normalization and Weight Decay. CoRR Ruosi Wan, Zhanxing Zhu, Xiangyu Zhang, Jian Sun
2020	C	`conf`	Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks. ACML Lei Wu, Zhanxing Zhu
2020	J	`jnl`	Using Generative Adversarial Networks to Break and Protect Text Captchas. ACM Trans. Priv. Secur. Guixin Ye, Zhanyong Tang, Dingyi Fang, Zhanxing Zhu, Yansong Feng, Pengfei Xu, Xiaojiang Chen, Jungong Han, Zheng Wang
2019	J	`jnl`	3D Graph Convolutional Networks with Temporal Graphs: A Spatial Information Free Framework For Traffic Forecasting. CoRR Bing Yu, Mengzhang Li, Jiyong Zhang, Zhanxing Zhu
2019	J	`jnl`	AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. CoRR Ke Sun, Zhouchen Lin, Zhanxing Zhu
2019	J	`jnl`	Bayesian Optimized Continual Learning with Attention Mechanism. CoRR Ju Xu, Jin Ma, Zhanxing Zhu
2019	J	`jnl`	Differentiable Neural Architecture Search via Proximal Iterations. CoRR Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu
2019	J	`jnl`	Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN. CoRR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2019	—	`conf`	How Question Generation Can Help Question Answering over Knowledge Base. NLPCC (1) Sen Hu, Lei Zou, Zhanxing Zhu
2019	A*	`conf`	Interpreting Adversarially Trained Convolutional Neural Networks. ICML Tianyuan Zhang, Zhanxing Zhu
2019	J	`jnl`	Interpreting Adversarially Trained Convolutional Neural Networks. CoRR Tianyuan Zhang, Zhanxing Zhu
2019	J	`jnl`	Multi-Stage Self-Supervised Learning for Graph Convolutional Networks. CoRR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2019	—	`conf`	Neural Control Variates for Monte Carlo Variance Reduction. ECML/PKDD (2) Ruosi Wan, Mingjun Zhong, Haoyi Xiong, Zhanxing Zhu
2019	J	`jnl`	On the Learning Dynamics of Two-layer Nonlinear Convolutional Neural Networks. CoRR Bing Yu, Junzhao Zhang, Zhanxing Zhu
2019	J	`jnl`	Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy. CoRR Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu
2019	J	`jnl`	Quasi-potential as an implicit regularizer for the loss function in the stochastic gradient descent. CoRR Wenqing Hu, Zhanxing Zhu, Haoyi Xiong, Jun Huan
2019	J	`jnl`	ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling. CoRR Bing Yu, Haoteng Yin, Zhanxing Zhu
2019	A*	`conf`	SpHMC: Spectral Hamiltonian Monte Carlo. AAAI Haoyi Xiong, Kafeng Wang, Jiang Bian, Zhanxing Zhu, Cheng-Zhong Xu, Zhishan Guo, Jun Huan
2019	J	`jnl`	Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling. CoRR He Wang, Edmond S. L. Ho, Hubert P. H. Shum, Zhanxing Zhu
2019	A*	`conf`	Tangent-Normal Adversarial Regularization for Semi-Supervised Learning. CVPR Bing Yu, Jingfeng Wu, Jinwen Ma, Zhanxing Zhu
2019	A*	`conf`	The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects. ICML Zhanxing Zhu, Jingfeng Wu, Bing Yu, Lei Wu, Jinwen Ma
2019	J	`jnl`	The Multiplicative Noise in Stochastic Gradient Descent: Data-Dependent Regularization, Continuous and Discrete Approximation. CoRR Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Zhanxing Zhu
2019	A*	`conf`	Towards Making Deep Transfer Learning Never Hurt. ICDM Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan
2019	J	`jnl`	Towards Making Deep Transfer Learning Never Hurt. CoRR Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan
2019	J	`jnl`	Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors. CoRR Ke Sun, Zhanxing Zhu, Zhouchen Lin
2019	—	`conf`	Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. PRCV (1) Ke Sun, Zhouchen Lin, Hantao Guo, Zhanxing Zhu
2019	J	`jnl`	Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. CoRR Ke Sun, Hantao Guo, Zhanxing Zhu, Zhouchen Lin
2019	A*	`conf`	You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle. NeurIPS Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong
2019	J	`jnl`	You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle. CoRR Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong
2018	A*	`conf`	Bayesian Adversarial Learning. NeurIPS Nanyang Ye, Zhanxing Zhu
2018	J	`jnl`	Neural Control Variates for Variance Reduction. CoRR Zhanxing Zhu, Ruosi Wan, Mingjun Zhong
2018	A*	`conf`	Reinforced Continual Learning. NeurIPS Ju Xu, Zhanxing Zhu
2018	J	`jnl`	Reinforced Continual Learning. CoRR Ju Xu, Zhanxing Zhu
2018	—	`conf`	SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction. ISBI Huizhuo Yuan, Jinzhu Jia, Zhanxing Zhu
2018	A*	`conf`	Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting. IJCAI Bing Yu, Haoteng Yin, Zhanxing Zhu
2018	A*	`conf`	Stochastic Fractional Hamiltonian Monte Carlo. IJCAI Nanyang Ye, Zhanxing Zhu
2018	J	`jnl`	Tangent-Normal Adversarial Regularization for Semi-supervised Learning. CoRR Bing Yu, Jingfeng Wu, Zhanxing Zhu
2018	J	`jnl`	The Regularization Effects of Anisotropic Noise in Stochastic Gradient Descent. CoRR Zhanxing Zhu, Jingfeng Wu, Bing Yu, Lei Wu, Jinwen Ma
2018	A*	`conf`	Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning. NeurIPS Rui Luo, Jianhong Wang, Yaodong Yang, Jun Wang, Zhanxing Zhu
2018	J	`jnl`	Understanding and Enhancing the Transferability of Adversarial Examples. CoRR Lei Wu, Zhanxing Zhu, Cheng Tai, Weinan E
2018	A*	`conf`	Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach. CCS Guixin Ye, Zhanyong Tang, Dingyi Fang, Zhanxing Zhu, Yansong Feng, Pengfei Xu, Xiaojiang Chen, Zheng Wang
2017	J	`jnl`	A Deep Learning-based Framework for Conducting Stealthy Attacks in Industrial Control Systems. CoRR Cheng Feng, Tingting Li, Zhanxing Zhu, Deeph Chana
2017	J	`jnl`	Langevin Dynamics with Continuous Tempering for High-dimensional Non-convex Optimization. CoRR Nanyang Ye, Zhanxing Zhu, Rafal K. Mantiuk
2017	—	`conf`	Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks. NIPS Nanyang Ye, Zhanxing Zhu, Rafal Mantiuk
2017	—	`conf`	Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix. ACL (1) Bingfeng Luo, Yansong Feng, Zheng Wang, Zhanxing Zhu, Songfang Huang, Rui Yan, Dongyan Zhao
2017	J	`jnl`	Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix. CoRR Bingfeng Luo, Yansong Feng, Zheng Wang, Zhanxing Zhu, Songfang Huang, Rui Yan, Dongyan Zhao
2017	J	`jnl`	Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting. CoRR Bing Yu, Haoteng Yin, Zhanxing Zhu
2017	J	`jnl`	Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes. CoRR Lei Wu, Zhanxing Zhu, Weinan E
2016	—	`—`	Integrating local information for inference and optimization in machine learning. Zhanxing Zhu
2016	A*	`conf`	Stochastic Parallel Block Coordinate Descent for Large-Scale Saddle Point Problems. AAAI Zhanxing Zhu, Amos J. Storkey
2015	—	`conf`	Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems. ECML/PKDD (1) Zhanxing Zhu, Amos J. Storkey
2015	J	`jnl`	Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems. CoRR Zhanxing Zhu, Amos J. Storkey
2015	—	`conf`	Aggregation Under Bias: Rényi Divergence Aggregation and Its Implementation via Machine Learning Markets. ECML/PKDD (1) Amos J. Storkey, Zhanxing Zhu, Jinli Hu
2015	—	`conf`	Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling. NIPS Xiaocheng Shang, Zhanxing Zhu, Benedict J. Leimkuhler, Amos J. Storkey
2015	J	`jnl`	Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling. CoRR Xiaocheng Shang, Zhanxing Zhu, Benedict J. Leimkuhler, Amos J. Storkey
2013	—	`conf`	Multiplicative Updates for Learning with Stochastic Matrices. SCIA Zhanxing Zhu, Zhirong Yang, Erkki Oja
2013	J	`jnl`	Supervised Distance Preserving Projections. Neural Process. Lett. Zhanxing Zhu, Timo Similä, Francesco Corona
2011	Misc	`conf`	Hyperspectral unmixing using non-negative matrix factorization with automatically estimating regularization parameters. ICNC Zhenwei Shi, Zhenyu An, Xueyan Tan, Zhanxing Zhu, Zhiguo Jiang
2010	Misc	`conf`	A method of automatically estimating the regularization parameter for Non-negative Matrix Factorization. ICNC Dalong Cheng, Zhenwei Shi, Xueyan Tan, Zhanxing Zhu, Zhiguo Jiang
2010	—	`conf`	Automatic Rank Determination in Projective Nonnegative Matrix Factorization. LVA/ICA Zhirong Yang, Zhanxing Zhu, Erkki Oja
2009	—	`conf`	A Fixed-Point Algorithm for Nonnegative Independent Component Analysis. ICNC (2) Zhenwei Shi, Xueyan Tan, Zhanxing Zhu, Zhiguo Jiang
2009	—	`conf`	Quadratic Form Innovation to Blind Source Separation. ICNC (2) Zhenwei Shi, Zhanxing Zhu, Xueyan Tan, Zhiguo Jiang