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FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders


Mar 26, 2021
Wei Chen, Kun Zhang, Ruichu Cai, Biwei Huang, Joseph Ramsey, Zhifeng Hao, Clark Glymour


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Towards advancing the earthquake forecasting by machine learning of satellite data


Jan 31, 2021
Pan Xiong, Lei Tong, Kun Zhang, Xuhui Shen, Roberto Battiston, Dimitar Ouzounov, Roberto Iuppa, Danny Crookes, Cheng Long, Huiyu Zhou


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Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction


Jan 20, 2021
Gang Qu, Li Xiao, Wenxing Hu, Kun Zhang, Vince D. Calhoun, Yu-Ping Wang


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Learning Disentangled Semantic Representation for Domain Adaptation


Dec 22, 2020
Ruichu Cai, Zijian Li, Pengfei Wei, Jie Qiao, Kun Zhang, Zhifeng Hao


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Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation


Dec 16, 2020
Chaochao Lu, Biwei Huang, Ke Wang, José Miguel Hernández-Lobato, Kun Zhang, Bernhard Schölkopf

* Neural Information Processing Systems Workshop on Offline Reinforcement Learning 

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R$^2$-Net: Relation of Relation Learning Network for Sentence Semantic Matching


Dec 16, 2020
Kun Zhang, Le Wu, Guangyi Lv, Meng Wang, Enhong Chen, Shulan Ruan

* This paper has been accepted to/by AAAI2021 

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Learning Heatmap-Style Jigsaw Puzzles Provides Good Pretraining for 2D Human Pose Estimation


Dec 13, 2020
Kun Zhang, Rui Wu, Ping Yao, Kai Deng, Ding Li, Renbiao Liu, Chuanguang Yang, Ge Chen, Min Du, Tianyao Zheng


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How Do Fair Decisions Fare in Long-term Qualification?


Oct 21, 2020
Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, Cheng Zhang

* Accepted to the 34th Conference on Neural Information Processing Systems (NeurIPS) 

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Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs


Oct 10, 2020
Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang


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Attack on Multi-Node Attention for Object Detection


Aug 16, 2020
Sizhe Chen, Fan He, Xiaolin Huang, Kun Zhang


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Adaptive Task Sampling for Meta-Learning


Jul 17, 2020
Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi

* ECCV2020 

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On the Role of Sparsity and DAG Constraints for Learning Linear DAGs


Jun 17, 2020
Ignavier Ng, AmirEmad Ghassami, Kun Zhang

* 24 pages, 10 figures 

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Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach


May 25, 2020
Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, Meng Wang

* Accepted by SIGIR2020 

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A Causal View on Robustness of Neural Networks


May 03, 2020
Cheng Zhang, Kun Zhang, Yingzhen Li


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Learning from Positive and Unlabeled Data by Identifying the Annotation Process


Mar 02, 2020
Naji Shajarisales, Peter Spirtes, Kun Zhang

* Submitted to UAI 2020 

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Domain Adaptation As a Problem of Inference on Graphical Models


Feb 14, 2020
Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Clark Glymour

* 17 pages; 6 figures 

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Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach


Jan 28, 2020
Lei Chen, Le Wu, Richang Hong, Kun Zhang, Meng Wang

* The updated version is publised in AAAI 2020 

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Deep Technology Tracing for High-tech Companies


Jan 02, 2020
Han Wu, Kun Zhang, Guangyi Lv, Qi Liu, Runlong Yu, Weihao Zhao, Enhong Chen, Jianhui Ma

* 6 pages, 7 figures 

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Tracing the Propagation Path: A Flow Perspective of Representation Learning on Graphs


Dec 12, 2019
Menghan Wang, Kun Zhang, Gulin Li, Keping Yang, Luo Si


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Transfer Learning-Based Outdoor Position Recovery with Telco Data


Dec 10, 2019
Yige Zhang, Aaron Yi Ding, Jorg Ott, Mingxuan Yuan, Jia Zeng, Kun Zhang, Weixiong Rao


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Deep Physiological State Space Model for Clinical Forecasting


Dec 04, 2019
Yuan Xue, Denny Zhou, Nan Du, Andrew Dai, Zhen Xu, Kun Zhang, Claire Cui


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Disentanglement Challenge: From Regularization to Reconstruction


Nov 30, 2019
Jie Qiao, Zijian Li, Boyan Xu, Ruichu Cai, Kun Zhang

* NeurIPS2019 Disentanglement Challenge 

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Modelling EHR timeseries by restricting feature interaction


Nov 14, 2019
Kun Zhang, Yuan Xue, Gerardo Flores, Alvin Rajkomar, Claire Cui, Andrew M. Dai

* Machine Learning for Health (ML4H) at NeurIPS 2019 - Extended Abstract 

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Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs


Oct 28, 2019
AmirEmad Ghassami, Kun Zhang, Negar Kiyavash


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DNANet: De-Normalized Attention Based Multi-Resolution Network for Human Pose Estimation


Oct 21, 2019
Kun Zhang, Peng He, Ping Yao, Ge Chen, Chuanguang Yang, Huimin Li, Li Fu, Tianyao Zheng


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Adversarial Orthogonal Regression: Two non-Linear Regressions for Causal Inference


Sep 10, 2019
M. Reza Heydari, Saber Salehkaleybar, Kun Zhang


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Gated Convolutional Networks with Hybrid Connectivity for Image Classification


Sep 08, 2019
Chuanguang Yang, Zhulin An, Hui Zhu, Xiaolong Hu, Kun Zhang, Kaiqiang Xu, Chao Li, Yongjun Xu


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Likelihood-Free Overcomplete ICA and Applications in Causal Discovery


Sep 05, 2019
Chenwei Ding, Mingming Gong, Kun Zhang, Dacheng Tao

* 10 pages, 3 figures. Accepted by NeurIPS 2019 as spotlight 

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