Zhitang Chen

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 80

Top Topics

Cellular Networks

Causal Discovery

Top Venues

Publications

Tim Tse, Zhitang Chen, Shengyu Zhu, Yue Liu
Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms. CoRR (2024)
Tim Tse, Isaac Chan, Zhitang Chen
Causal Coordinated Concurrent Reinforcement Learning. CoRR (2024)
Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He
On Low-Rank Directed Acyclic Graphs and Causal Structure Learning. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao
A Unified Framework for Layout Pattern Analysis With Deep Causal Estimation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (4) (2023)
Junlong Lyu, Zhitang Chen, Wenlong Lyu, Jianye Hao
Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization. CoRR (2023)
Wenlong Lyu, Shoubo Hu, Jie Chuai, Zhitang Chen
Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets. CoRR (2023)
Yunqi Wang, Furui Liu, Zhitang Chen, Yik-Chung Wu, Jianye Hao, Guangyong Chen, Pheng-Ann Heng
Contrastive-ACE: Domain Generalization Through Alignment of Causal Mechanisms. IEEE Trans. Image Process. 32 (2023)
Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. CoRR (2023)
Siting Liu, Yuan Pu, Peiyu Liao, Hongzhong Wu, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu
FastGR: Global Routing on CPU-GPU With Heterogeneous Task Graph Scheduler. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (7) (2023)
Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen
Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs. CoRR (2023)
Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. AAAI (2023)
Siting Liu, Yuan Pu, Peiyu Liao, Hongzhong Wu, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu
FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler (Extended Abstract). IJCAI (2023)
Kaiwen Zhou, Zhilin Chen, Guochen Liu, Zhitang Chen
A Novel Extrapolation Technique to Accelerate WMMSE. ICASSP (2023)
Junlong Lyu, Zhitang Chen, Shoubo Feng
Convergence guarantee for consistency models. CoRR (2023)
Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen
Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs. NeurIPS (2023)
Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang
Weakly Supervised Disentangled Generative Causal Representation Learning. J. Mach. Learn. Res. 23 (2022)
Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Yongwei Chen
Universality of parametric Coupling Flows over parametric diffeomorphisms. CoRR (2022)
Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen
Reframed GES with a neural conditional dependence measure. UAI (2022)
Siting Liu, Peiyu Liao, Rui Zhang, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu
FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler. DATE (2022)
Lin Yang, Min Cheng, Jun Qu, Zhitang Chen
GraphHO: A Graph-based Handover Optimization System for Cellular Networks. ISWCS (2022)
Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen
Reframed GES with a Neural Conditional Dependence Measure. CoRR (2022)
Ignavier Ng, Shengyu Zhu, Zhuangyan Fang, Haoyang Li, Zhitang Chen, Jun Wang
Masked Gradient-Based Causal Structure Learning. SDM (2022)
Xiaopeng Zhang, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Evangeline F. Y. Young, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao
RCANet: Root Cause Analysis via Latent Variable Interaction Modeling for Yield Improvement. ITC (2022)
Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Chen Yongwei
Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates. NeurIPS (2022)
Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu
Out-of-distribution Generalization with Causal Invariant Transformations. CVPR (2022)
Ruoyu Wang, Mingyang Yi, Zhitang Chen, Shengyu Zhu
Out-of-distribution Generalization with Causal Invariant Transformations. CoRR (2022)
Mengyue Yang, Xinyu Cai, Furui Liu, Xu Chen, Zhitang Chen, Jianye Hao, Jun Wang
Generalizable Information Theoretic Causal Representation. CoRR (2022)
Chang Feng, Wenlong Lyu, Zhitang Chen, Junjie Ye, Mingxuan Yuan, Jianye Hao
Batch Sequential Black-Box Optimization with Embedding Alignment Cells for Logic Synthesis. ICCAD (2022)
Peiyu Liao, Siting Liu, Zhitang Chen, Wenlong Lv, Yibo Lin, Bei Yu
DREAMPlace 4.0: Timing-driven Global Placement with Momentum-based Net Weighting. DATE (2022)
Mengyue Yang, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, Jun Wang
CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models. CVPR (2021)
Yang Li, Zhitang Chen, Guochen Liu, Yik-Chung Wu, Kai-Kit Wong
Learning to Construct Nested Polar Codes: An Attention-Based Set-to-Element Model. IEEE Commun. Lett. 25 (12) (2021)
Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang
Ordering-Based Causal Discovery with Reinforcement Learning. IJCAI (2021)
Xiangle Cheng, James He, Shihan Xiao, Yingxue Zhang, Zhitang Chen, Pascal Poupart, Fenglin Li
Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks. CoRR (2021)
Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander Imani Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. CoRR (2021)
Ran Chen, Shoubo Hu, Zhitang Chen, Shengyu Zhu, Bei Yu, Pengyun Li, Cheng Chen, Yu Huang, Jianye Hao
A Unified Framework for Layout Pattern Analysis with Deep Causal Estimation. ICCAD (2021)
Keli Zhang, Shengyu Zhu, Marcus Kalander, Ignavier Ng, Junjian Ye, Zhitang Chen, Lujia Pan
gCastle: A Python Toolbox for Causal Discovery. CoRR (2021)
Yunqi Wang, Furui Liu, Zhitang Chen, Qing Lian, Shoubo Hu, Jianye Hao, Yik-Chung Wu
Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms. CoRR (2021)
Xiaoqiang Wang, Yali Du, Shengyu Zhu, Liangjun Ke, Zhitang Chen, Jianye Hao, Jun Wang
Ordering-Based Causal Discovery with Reinforcement Learning. CoRR (2021)
Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang
Asymptotically Optimal One- and Two-Sample Testing With Kernels. IEEE Trans. Inf. Theory 67 (4) (2021)
Vahid Partovi Nia, Xinlin Li, Masoud Asgharian, Shoubo Hu, Zhitang Chen, Yanhui Geng
Clustering Causal Additive Noise Models. CoRR (2020)
Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen
Stable Learning via Differentiated Variable Decorrelation. KDD (2020)
Yifei Wang, Dan Peng, Furui Liu, Zhenguo Li, Zhitang Chen, Jiansheng Yang
Decoder-free Robustness Disentanglement without (Additional) Supervision. CoRR (2020)
Minne Li, Mengyue Yang, Furui Liu, Xu Chen, Zhitang Chen, Jun Wang
Causal World Models by Unsupervised Deconfounding of Physical Dynamics. CoRR (2020)
Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He
Low Rank Directed Acyclic Graphs and Causal Structure Learning. CoRR (2020)
Haonan Duan, Abdullah Rashwan, Pascal Poupart, Zhitang Chen
Discriminative training of feed-forward and recurrent sum-product networks by extended Baum-Welch. Int. J. Approx. Reason. 124 (2020)
Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang
Disentangled Generative Causal Representation Learning. CoRR (2020)
Shengyu Zhu, Ignavier Ng, Zhitang Chen
Causal Discovery with Reinforcement Learning. ICLR (2020)
Mengyue Yang, Furui Liu, Zhitang Chen, Xinwei Shen, Jianye Hao, Jun Wang
CausalVAE: Structured Causal Disentanglement in Variational Autoencoder. CoRR (2020)
Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan
Domain Generalization via Multidomain Discriminant Analysis. CoRR (2019)
Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen
Masked Gradient-Based Causal Structure Learning. CoRR (2019)
Ignavier Ng, Shengyu Zhu, Zhitang Chen, Zhuangyan Fang
A Graph Autoencoder Approach to Causal Structure Learning. CoRR (2019)
Zhitang Chen, Zhongpeng Wang, Kun Wang, Weibo Yi, Hongzhi Qi
Recognizing Motor Imagery Between Hand and Forearm in the Same Limb in a Hybrid Brain Computer Interface Paradigm: An Online Study. IEEE Access 7 (2019)
Shoubo Hu, Bogdan Cautis, Zhitang Chen, Laiwan Chan, Yanhui Geng, Xiuqiang He
Model-free inference of diffusion networks using RKHS embeddings. Data Min. Knowl. Discov. 33 (2) (2019)
Shengyu Zhu, Zhitang Chen
Causal Discovery with Reinforcement Learning. CoRR (2019)
Shengyu Zhu, Biao Chen, Zhitang Chen, Pengfei Yang
Asymptotically Optimal One- and Two-Sample Testing with Kernels. CoRR (2019)
Jie Chuai, Zhitang Chen, Guochen Liu, Xueying Guo, Xiaoxiao Wang, Xin Liu, Chongming Zhu, Feiyi Shen
A Collaborative Learning Based Approach for Parameter Configuration of Cellular Networks. INFOCOM (2019)
Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan
Domain Generalization via Multidomain Discriminant Analysis. UAI (2019)
Xiaoxiao Wang, Xueying Guo, Jie Chuai, Zhitang Chen, Xin Liu
Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration. IEEE BigData (2019)
Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. AISTATS (2019)
Zhitang Chen, Shengyu Zhu, Yue Liu, Tim Tse
Causal Discovery by Kernel Intrinsic Invariance Measure. CoRR (2019)
Thomas G. Dietterich, George Trimponias, Zhitang Chen
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning. ICML (2018)
Shengyu Zhu, Biao Chen, Zhitang Chen
Exponentially Consistent Kernel Two-Sample Tests. CoRR (2018)
Shoubo Hu, Zhitang Chen, Laiwan Chan
A Kernel Embedding-based Approach for Nonstationary Causal Model Inference. CoRR (2018)
Shoubo Hu, Zhitang Chen, Laiwan Chan
A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference. Neural Comput. 30 (5) (2018)
Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Laiwan Chan, Yanhui Geng
Causal Inference and Mechanism Clustering of a Mixture of Additive Noise Models. CoRR (2018)
Thomas G. Dietterich, George Trimponias, Zhitang Chen
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning. CoRR (2018)
Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Lai-Wan Chan, Yanhui Geng
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models. NeurIPS (2018)
Abdullah Rashwan, Pascal Poupart, Zhitang Chen
Discriminative Training of Sum-Product Networks by Extended Baum-Welch. PGM (2018)
Xiaoxiao Wang, Xueying Guo, Jie Chuai, Zhitang Chen, Xin Liu
Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration. CoRR (2018)
Zhuoshu Li, Zhitang Chen, Pascal Poupart, Sanmay Das, Yanhui Geng
Faster Policy Adaptation in Environments with Exogeneity: A State Augmentation Approach. AAMAS (2018)
Xueying Guo, George Trimponias, Xiaoxiao Wang, Zhitang Chen, Yanhui Geng, Xin Liu
Learning-Based Joint Configuration for Cellular Networks. IEEE Internet Things J. 5 (6) (2018)
Shengyu Zhu, Biao Chen, Pengfei Yang, Zhitang Chen
Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit. CoRR (2018)
Zhitang Chen, Xin Zhao, Zhongpeng Wang, Kun Wang, Weibo Yi, Feng He, Hongzhi Qi
A Hybrid Brain Computer Interface Driven by Motor Imagery of Right Hand Versus Right Forearm. iCAST (2018)
Xueying Guo, George Trimponias, Xiaoxiao Wang, Zhitang Chen, Yanhui Geng, Xin Liu
Cellular network configuration via online learning and joint optimization. IEEE BigData (2017)
Zhitang Chen, Ke He, Jian Li, Yanhui Geng
Seq2Img: A sequence-to-image based approach towards IP traffic classification using convolutional neural networks. IEEE BigData (2017)
Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart
Online Bayesian Transfer Learning for Sequential Data Modeling. ICLR (Poster) (2017)
Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart
Online Algorithms for Sum-Product Networks with Continuous Variables. Probabilistic Graphical Models (2016)
Pascal Poupart, Zhitang Chen, Priyank Jaini, Fred Fung, Hengky Susanto, Yanhui Geng, Li Chen, Kai Chen, Hao Jin
Online flow size prediction for improved network routing. ICNP (2016)
Zhitang Chen, Jiayao Wen, Yanhui Geng
Predicting future traffic using Hidden Markov Models. ICNP (2016)
Zhitang Chen, Pascal Poupart, Yanhui Geng
Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings. AISTATS (2016)
Zhitang Chen, Kun Zhang, Laiwan Chan, Bernhard Schölkopf
Causal Discovery via Reproducing Kernel Hilbert Space Embeddings. Neural Comput. 26 (7) (2014)
Zhitang Chen, Kun Zhang, Laiwan Chan
Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method. ICDM (2013)
Zhitang Chen, Laiwan Chan
Causality in Linear Nongaussian Acyclic Models in the Presence of Latent Gaussian Confounders. Neural Comput. 25 (6) (2013)
Zhitang Chen, Kun Zhang, Laiwan Chan
Causal discovery with scale-mixture model for spatiotemporal variance dependencies. NIPS (2012)
Zhitang Chen, Laiwan Chan
Causal Discovery for Linear Non-Gaussian Acyclic Models in the Presence of Latent Gaussian Confounders. LVA/ICA (2012)
Zhitang Chen, Laiwan Chan
New approaches for solving permutation indeterminacy and scaling ambiguity in frequency domain separation of convolved mixtures. IJCNN (2011)