Yatao Bian(卞亚涛)

Senior Research Scientist

Tencent AI Lab

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I am interested in topics including deep graph neural nets, drug development, continuous & combinatorial optimization and decentralized AI. I like various sports, e.g., swimming, hiking & skiing.

Papers23 papers

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Self-Supervised Graph Transformer on Large-Scale Molecular Data

Yu Rong,Yatao Bian,Tingyang Xu, Weiyang Xie,Ying Wei,Wenbing Huang,Junzhou Huang

NeurIPS, (2020)

EIBibtex

On Self-Distilling Graph Neural Network

Yuzhao Chen,Yatao Bian, Xi Xiao,Yu Rong,Tingyang Xu,Junzhou Huang

Bibtex

Graph Information Bottleneck for Subgraph Recognition

Junchi Yu,Tingyang Xu,Yu Rong,Yatao Bian,Junzhou Huang,Ran He

international conference on learning representations, (2020)

Bibtex

Self-Supervised Graph Transformer on Large-Scale Molecular Data

Yu Rong,Yatao Bian,Tingyang Xu,Weiyang Xie,Ying WEI,Wenbing Huang,Junzhou Huang

NIPS 2020, (2020)

Bibtex

Multi-View Graph Neural Networks for Molecular Property Prediction

Hehuan Ma,Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye, Junzhou Huang

arXiv preprint arXiv:2005.13607, (2020)

Cited by2Bibtex

GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data

Yu Rong,Yatao Bian,Tingyang Xu,Weiyang Xie,Ying Wei,Wenbing Huang,Junzhou Huang

Bibtex

Continuous Submodular Function Maximization

Yatao Bian,Joachim M. Buhmann,Andreas Krause

Cited by1Bibtex

From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models

Sahin Aytunc,Bian Yatao,Buhmann Joachim M.,Krause Andreas

ICML, pp.8388-8397, (2020)

Cited by1EIBibtex

Provable Non-Convex Optimization and Algorithm Validation via Submodularity

Bian Yatao An

Cited by1Bibtex

Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference

Yatao Bian,Joachim M. Buhmann,Andreas Krause

pp.644-653 (2019)

Cited by17EIBibtex

Parallel Coordinate Descent Newton Method for Efficient $L_1$-Regularized Loss Minimization

Yatao An Bian,Xiong Li,Yuncai Liu,Ming-Hsuan Yang

IEEE transactions on neural networks and learning systems, no. 11 (2019): 3233-3245

Cited by10WOSEIBibtex

COLA: Communication-Efficient Decentralized Linear Learning

Lie He,An Bian,Martin Jaggi

arXiv: Distributed, Parallel, and Cluster Computing, (2018)

Cited by48EIBibtex

A Distributed Second-Order Algorithm You Can Trust

Celestine Dünner,Aurélien Lucchi, Matilde Gargiani,An Bian,Thomas Hofmann,Martin Jaggi

ICML, (2018): 1357-1365

Cited by18EIBibtex

Continuous DR-submodular Maximization: Structure and Algorithms

An Bian,Kfir Y. Levy,Andreas Krause,Joachim M. Buhmann

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), (2017): 486-496

Cited by32Bibtex

Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains

Yatao Bian,Baharan Mirzasoleiman,Joachim M. Buhmann,Andreas Krause 0001

AISTATS, (2017): 111-120

Cited by79EIBibtex

Information-theoretic analysis of MaxCut algorithms

Yatao Bian,Alexey Gronskiy,Joachim M. Buhmann

ITA, pp.1-5, (2016)

Cited by4EIBibtex

Greedy MaxCut algorithms and their information content

Yatao Bian,Alexey Gronskiy,Joachim M. Buhmann

Information Theory Workshop, (2015)

Cited by7EIWOSBibtex

Parallel Coordinate Descent Newton Method for Efficient $\ell_1$-Regularized Minimization

Yatao Bian,Xiong Li,Yuncai Liu,Minghsuan Yang

(2013)

Cited by3Bibtex

Parallel Coordinate Descent Newton for Large-scale L1-Regularized Minimization

Yatao Bian,Xiong Li,Yuncai Liu

CoRR, (2013)

Cited by6EIBibtex

Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression

Yatao Bian,Xiong Li,Mingqi Cao,Yuncai Liu

ECML/PKDD (3), no. PART 3 (2013): 81-95

Cited by9WOSSCOPUSEIBibtex

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Yatao Bian(卞亚涛)Binding

Papers23 papers

Yatao Bian(卞亚涛)