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Decoupling Representation and Classifier for Noisy Label Learning

Nov 16, 2020
Hui Zhang, Quanming Yao


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A Survey of Label-noise Representation Learning: Past, Present and Future

Nov 09, 2020
Bo Han, Quanming Yao, Tongliang Liu, Gang Niu, Ivor W. Tsang, James T. Kwok, Masashi Sugiyama

* The draft is kept updating; any comments and suggestions are welcome 

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Graph Neural Network with Automorphic Equivalence Filters

Nov 09, 2020
Fengli Xu, Quanming Yao, Pan Hui, Yong Li


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Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration

Oct 24, 2020
Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan Zhang, Liangpei Zhang

* Accepted to TPAMI 

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Efficient, Simple and Automated Negative Sampling for Knowledge Graph Embedding

Oct 24, 2020
Yongqi Zhang, Quanming Yao, Lei Chen

* VLDB Journal accepted. arXiv admin note: text overlap with arXiv:1812.06410 

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Propagation Model Search for Graph Neural Networks

Oct 07, 2020
Yuhui Ding, Quanming Yao, Tong Zhang

* 10 pages 

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Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering

Sep 07, 2020
Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, Depeng Jin

* 20 pages, 7 figures, 8 tables 

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Simplifying Architecture Search for Graph Neural Network

Sep 06, 2020
Huan Zhao, Lanning Wei, Quanming Yao

* CIKM 2020 Workshop: 1st Workshop Combining Symbolic and Subsymbolic Methods and their Applications 

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Efficient Low-Rank Matrix Learning by Factorizable Nonconvex Regularization

Aug 22, 2020
Yaqing Wang, Quanming Yao, James T. Kwok


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Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases

Jul 08, 2020
Yu Liu, Quanming Yao, Yong Li

* WWW 2020 

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Efficient Backbone Search for Scene Text Recognition

Mar 14, 2020
Hui Zhang, Quanming Yao, Mingkun Yang, Yongchao Xu, Xiang Bai


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Neural Recurrent Structure Search for Knowledge Graph Embedding

Nov 17, 2019
Yongqi Zhang, Quanming Yao, Lei Chen


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Searching to Exploit Memorization Effect in Learning from Corrupted Labels

Nov 06, 2019
Hansi Yang, Quanming Yao, Bo Han, Gang Niu


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Searching for Interaction Functions in Collaborative Filtering

Jun 28, 2019
Quanming Yao, Xiangning Chen, James Kwok, Yong Li


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AutoKGE: Searching Scoring Functions for Knowledge Graph Embedding

Jun 03, 2019
Yongqi Zhang, Quanming Yao, Wenyuan Dai, Lei Chen


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Differentiable Neural Architecture Search via Proximal Iterations

May 30, 2019
Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu


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Generalizing from a Few Examples: A Survey on Few-Shot Learning

May 13, 2019
Yaqing Wang, Quanming Yao, James Kwok, Lionel M. Ni


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Robust Learning from Noisy Side-information by Semidefinite Programming

May 12, 2019
En-Liang Hu, Quanming Yao

* arXiv admin note: text overlap with arXiv:1203.3461 by other authors 

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Few-shot Learning: A Survey

Apr 10, 2019
Yaqing Wang, Quanming Yao


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NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding

Jan 18, 2019
Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen


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Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising

Dec 11, 2018
Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao


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Privacy-preserving Transfer Learning for Knowledge Sharing

Nov 23, 2018
Xiawei Guo, Quanming Yao, WeiWei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang


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Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

Oct 30, 2018
Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, Masashi Sugiyama

* NIPS 2018 camera-ready version 

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Scalable Tensor Completion with Nonconvex Regularization

Sep 05, 2018
Quanming Yao, James T Kwok, Bo Han, Weiwei Tu


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Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers

Jul 23, 2018
Quanming Yao, James T. Kwok, Taifeng Wang, Tie-Yan Liu

* Accepted by TPAMI in 2018 (extension of ICDM-2015 conference paper arXiv:1512.00984) 

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Online Convolutional Sparse Coding with Sample-Dependent Dictionary

Jun 07, 2018
Yaqing Wang, Quanming Yao, James T. Kwok, Lionel M. Ni

* Accepted by ICML-2018 

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Loss-aware Binarization of Deep Networks

May 10, 2018
Lu Hou, Quanming Yao, James T. Kwok


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