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Self-adaptive Multi-task Particle Swarm Optimization


Oct 09, 2021
Xiaolong Zheng, Deyun Zhou, Na Li, Yu Lei, Tao Wu, Maoguo Gong


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Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding


Sep 10, 2021
Zhenzhi Wang, Limin Wang, Tao Wu, Tianhao Li, Gangshan Wu

* 18 pages, 18 figures. 1st place solution to HC-STVG challenge of the 3rd PIC workshop (http://www.picdataset.com/challenge/task/hcvg/

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Microsoft Recommenders: Tools to Accelerate Developing Recommender Systems


Aug 27, 2020
Scott Graham, Jun-Ki Min, Tao Wu

* Proceedings of the 13th ACM Conference on Recommender Systems (2019) 
* pages: 2; submitted to: RecSys '19 

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Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval


Aug 19, 2020
Tao Wu, Ellie Ka-In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao

* Accepted at CIKM 2020 

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Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds


May 06, 2020
Li Wang, Dawei Zhao, Tao Wu, Hao Fu, Zhiyu Wang, Liang Xiao, Xin Xu, Bin Dai


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Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning


Feb 27, 2020
Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers

* Presented at the 23 rd International Conference on Artificial Intelligence and Statistics (AISTATS) 2020. Code: https://github.com/zhenzhangye/graph_TV_recond 

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Modeling Information Need of Users in Search Sessions


Jan 03, 2020
Kishaloy Halder, Heng-Tze Cheng, Ellie Ka In Chio, Georgios Roumpos, Tao Wu, Ritesh Agarwal


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Informative GANs via Structured Regularization of Optimal Transport


Dec 04, 2019
Pierre Bréchet, Tao Wu, Thomas Möllenhoff, Daniel Cremers

* Presented at the Optimal Transport and Machine Learning Workshop, NeurIPS 2019 

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Variational Uncalibrated Photometric Stereo under General Lighting


Apr 08, 2019
Bjoern Haefner, Zhenzhang Ye, Maolin Gao, Tao Wu, Yvain Quéau, Daniel Cremers

* Haefner and Ye contributed equally 

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Optimization of Inf-Convolution Regularized Nonconvex Composite Problems


Mar 27, 2019
Emanuel Laude, Tao Wu, Daniel Cremers

* Accepted as a Conference Paper to International Conference on Artificial Intelligence and Statistics (AISTATS) 2019, Naha 

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Probabilistic Discriminative Learning with Layered Graphical Models


Jan 31, 2019
Yuesong Shen, Tao Wu, Csaba Domokos, Daniel Cremers


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Network Reconstruction and Controlling Based on Structural Regularity Analysis


Aug 29, 2018
Tao Wu, Shaojie Qiao, Xingping Xian, Xi-Zhao Wang, Wei Wang, Yanbing Liu


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Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform


Aug 06, 2018
Lingni Ma, Jörg StĂŒckler, Tao Wu, Daniel Cremers

* This work was first submitted to NIPS 2017, May 2017 

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Combinatorial Preconditioners for Proximal Algorithms on Graphs


Feb 21, 2018
Thomas Möllenhoff, Zhenzhang Ye, Tao Wu, Daniel Cremers

* Published as a conference paper at AISTATS 2018 

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LED-based Photometric Stereo: Modeling, Calibration and Numerical Solution


Sep 04, 2017
Yvain Quéau, Bastien Durix, Tao Wu, Daniel Cremers, François Lauze, Jean-Denis Durou


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Retrospective Higher-Order Markov Processes for User Trails


Apr 20, 2017
Tao Wu, David Gleich


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Multi-way Monte Carlo Method for Linear Systems


Aug 15, 2016
Tao Wu, David F. Gleich


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