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Linglong Kong

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Gaussian Differential Privacy on Riemannian Manifolds

Nov 09, 2023
Yangdi Jiang, Xiaotian Chang, Yi Liu, Lei Ding, Linglong Kong, Bei Jiang

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Mathematical Challenges in Deep Learning

Mar 24, 2023
Vahid Partovi Nia, Guojun Zhang, Ivan Kobyzev, Michael R. Metel, Xinlin Li, Ke Sun, Sobhan Hemati, Masoud Asgharian, Linglong Kong, Wulong Liu, Boxing Chen

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Conformalized Fairness via Quantile Regression

Oct 05, 2022
Meichen Liu, Lei Ding, Dengdeng Yu, Wulong Liu, Linglong Kong, Bei Jiang

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How Does Value Distribution in Distributional Reinforcement Learning Help Optimization?

Sep 29, 2022
Ke Sun, Bei Jiang, Linglong Kong

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Distributional Reinforcement Learning via Sinkhorn Iterations

Feb 16, 2022
Ke Sun, Yingnan Zhao, Yi Liu, Bei Jiang, Linglong Kong

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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

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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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