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Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving

Dec 09, 2021
Lei Ding, Dengdeng Yu, Jinhan Xie, Wenxing Guo, Shenggang Hu, Meichen Liu, Linglong Kong, Hongsheng Dai, Yanchun Bao, Bei Jiang

* Accepted by AAAI 2022 

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TAG: Toward Accurate Social Media Content Tagging with a Concept Graph

Oct 24, 2021
Jiuding Yang, Weidong Guo, Bang Liu, Yakun Yu, Chaoyue Wang, Jinwen Luo, Linglong Kong, Di Niu, Zhen Wen

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Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization

Oct 20, 2021
Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong

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Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm

Oct 07, 2021
Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Aref Sadeghi, Xiaodong Yan, Bei Jiang, Linglong Kong

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L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning

Sep 25, 2021
Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

* Accepted as a Full Research Paper at CIKM 2021; 10 pages, 3 Figures, 5 Tables 

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A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning

Sep 21, 2021
Hongming Zhang, Ke Sun, Bo Xu, Linglong Kong, Martin Müller

* 15 pages, 18 figures 

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Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations

Sep 17, 2021
Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, Linglong Kong

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Learning Privately over Distributed Features: An ADMM Sharing Approach

Jul 17, 2019
Yaochen Hu, Peng Liu, Linglong Kong, Di Niu

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Distributional Reinforcement Learning for Efficient Exploration

May 13, 2019
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu

* ICML, 2019 

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Deep Reinforcement Learning with Decorrelation

Mar 18, 2019
Borislav Mavrin, Hengshuai Yao, Linglong Kong

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QUOTA: The Quantile Option Architecture for Reinforcement Learning

Nov 07, 2018
Shangtong Zhang, Borislav Mavrin, Linglong Kong, Bo Liu, Hengshuai Yao

* AAAI 2019 

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Growing Story Forest Online from Massive Breaking News

Mar 01, 2018
Bang Liu, Di Niu, Kunfeng Lai, Linglong Kong, Yu Xu

* Accepted by CIKM 2017, 9 pages 

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Expectile Matrix Factorization for Skewed Data Analysis

Mar 03, 2017
Rui Zhu, Di Niu, Linglong Kong, Zongpeng Li

* 8 page main text with 5 page supplementary documents, published in AAAI 2017 

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Local Region Sparse Learning for Image-on-Scalar Regression

May 27, 2016
Yao Chen, Xiao Wang, Linglong Kong, Hongtu Zhu

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