Publications
2020

W. He, Q. Yao, C. Li, N. Yokoya, Q. Zhao, H. Zhang, L. Zhang.
Nonlocal Meets Global: An Integrated Paradigm for Hyperspectral Restoration.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
 Y. Zhang, Q. Yao, L. Chen.
Simple and Automated Negative Sampling for Knowledge Graph Embedding.
The International Journal on Very Large Data Bases (VLDBJ).
 H. Zhang, Q. Yao, M. Yang, Y. Xu, X. Bai.
AutoSTR: Efficient Backbone Search for Scene Text Recognition.
European Conference on Computer Vision (ECCV).
(paper,
code)
 Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok.
Searching to Exploit Memorization Effect in Learning from Noisy Labels.
International Conference on Machine Learning (ICML).
(paper,
code)
 B. Han, G. Niu, X. Yu, Q. Yao, M. Xu, I. Tsang, M. Sugiyama.
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust.
International Conference on Machine Learning (ICML).
(paper)
 Y. Wang, Q. Yao, J. Kwok, L. Ni.
Generalizing from a Few Examples: A Survey on FewShot Learning.
ACM Computing Surveys (CSUR).
(paper,
updatetodate reference list)
 Q. Yao, X. Chen, J. Kwok, Y. Li, C.J. Hsieh.
Efficient Neural Interaction Functions Search for Collaborative Filtering.
The Web Conference (WWW).
(paper,
code)
 Y. Liu, Q. Yao, Y. Li.
Generalizing Tensor Decomposition for Nary Relational Knowledge Bases.
The Web Conference (WWW).
(paper,
code)
 Q. Yao, J. Xu, W. Tu, Z. Zhu.
Efficient Neural Architecture Search via Proximal Iterations.
AAAI Conference on Artificial Intelligence (AAAI).
(paper,
code)
 Y. Zhang, Q. Yao, W. Dai, L. Chen.
AutoSF: Searching Scoring Functions for Knowledge Graph Embedding.
IEEE International Conference on Data Engineering (ICDE).
(paper,
code)

H. Shi,
Q. Yao,
Q. Guo,
Y. Li,
L. Zhang,
J. Ye,
Y. Li,
Y. Liu.
Predicting OriginDestination Flow via MultiPerspective Graph Convolutional Network.
IEEE International Conference on Data Engineering (ICDE).
(paper)
2019
 Q. Yao, J. Kwok, T. Wang, T. Liu.
LargeScale LowRank Matrix Learning with Nonconvex Regularizers.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
(paper;
Matlab code,
C++ code)
 Q. Yao, J. Kwok.
Accelerated and Inexact SoftImpute for LargeScale Matrix and Tensor Completion.
IEEE Transactions on Knowledge and Data Engineering (TKDE).
(paper;
code for matrix completion,
code for tensor completion)
 E. Hu, Q. Yao.
Robust Learning from Noisy Sideinformation by Semidefinite Programming.
International Joint Conference on Artificial Intelligence (IJCAI).
(paper)
 Q. Yao, X. Guo, J. Kwok, W. Tu, Y. Chen, D. Wen, Q. Yang.
Differential Private Stack Generalization with an Application to Diabetes Prediction.
International Joint Conference on Artificial Intelligence (IJCAI).
(paper,
slides)
 H. Shi, C. Zhang, Q. Yao, Y. Li, F. Sun, D. Jin.
StateSharing Sparse Hidden Markov Models for Personalized Sequences.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).
(paper,
slides)
 Y. Luo, M. Wang, H. Zhou, Q. Yao, W. Tu, Y. Chen, Q. Yang, W. Dai.
AutoCross: Automatic Feature Crossing for Tabular Data in RealWorld Applications.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).
(paper,
benchmark data,
3 mins video)
 Q. Yao, J. Kwok, B. Han.
Efficient Nonconvex Regularized Tensor Completion with Structureaware Proximal Iterations.
International Conference on Machine Learning (ICML).
(paper,
appendix,
code,
slides and 5 mins video)
 W. He, Q. Yao, C. Li, N. Yokoya, Q. Zhao.
Nonlocal Meets Global: An Integrated Paradigm for Hyperspectral Denoising.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR, oral).
(paper,
code)
 Y. Zhang, Q. Yao, Y. Shao, L. Chen.
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding.
IEEE International Conference on Data Engineering (ICDE).
(paper;
code)
[Top10 cited paper in ICDE 2019]
2018
 Q. Yao, J. Kwok.
Efficient Learning with Nonconvex Regularizers by Nonconvexity Redistribution.
Journal of Machine Learning Research (JMLR).
(paper;
code)
 Y. Wang, Q. Yao, J. Kwok, L. Ni.
Scalable Online Convolutional Sparse Coding.
IEEE Transactions on Image Processing (TIP).
(paper;
code)
 B. Han, Q. Yao, Y. Pan, I. Tsang, X. Xiao, Q. Yang, M. Sugiyama.
Millionaire: A Hintguided Approach for Crowdsourcing.
Machine Learning (MLJ).
(paper)
 Q. Yao, J. Kwok.
Scalable Robust Matrix Factorization with Nonconvex Loss.
Advance in Neural Information Processing Systems (NeurIPS).
(paper)
 B. Han, Q. Yao, X. Yu, G. Niu, M. Xu, W. Hu, I. Tsang, M. Sugiyama.
Coteaching: Robust training deep neural networks with extremely noisy labels.
Advance in Neural Information Processing Systems (NeurIPS).
(paper,
slides;
code)
[Top15 cited paper in NeurIPS 2018]
 Y. Wang, Q. Yao, J. Kwok, L. Ni.
Online Convolutional Sparse Coding with SampleDependent Dictionary.
International Conference on Machine Learning (ICML).
(paper; code)
2017
 H. Zhao, Q. Yao, J. Kwok, D. Lee.
Collaborative Filtering with Social Local Models.
IEEE International Conference on Data Mining (ICDM).
(paper)
 H. Zhao, Q. Yao, J. Li, Y. Song, D. Lee.
MetaGraph Based Recommendation Fusion over Heterogeneous Information Networks.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).
(paper;
code)
[Top15 cited paper in KDD 2017]
 Q. Yao, J. Kwok. F. Gao, W. Chen, T. Liu.
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems.
International Joint Conference on Artificial Intelligence (IJCAI).
(paper;
code)
 L. Hou, Q. Yao, J. Kwok.
Lossaware Binarization of Deep Networks.
International Conference on Learning Representations (ICLR).
(paper;
code)
 Y. Wang, J. Kwok, Q. Yao, L. Ni.
ZeroShot Learning with a Partial Set of Observed Attributes.
International Joint Conference on Neural Networks (IJCNN).
(paper)
 X. Guo, Q. Yao, J. Kwok.
Efficient Sparse LowRank Tensor Completion using FrankWolfe Algorithm.
AAAI Conference on Artificial Intelligence (AAAI).
(paper,
code)
 Y. Yang, Q. Yao, H. Qu.
VISTopic: A Visual Analytics System for Making Sense of Large Document Collections using Hierarchical Topic Modeling.
Journal of Visual Informatics.
(paper)
2016
 Q. Yao, J. Kwok.
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity.
International Conference on Machine Learning (ICML).
(paper;
code)
 Q. Yao, J. Kwok.
Greedy Learning of Generalized LowRank Models.
International Joint Conference on Artificial Intelligence (IJCAI).
(paper,
appendix)
2015
 Q. Yao, J. Kwok, W. Zhong.
Fast LowRank Matrix Learning with Nonconvex Regularization.
IEEE International Conference on Data Mining (ICDM).
(paper,
slide;
code)
 Q. Yao, J. Kwok.
Accelerated Inexact SoftImpute for Fast LargeScale Matrix Completion.
International Joint Conference on Artificial Intelligence (IJCAI).
(paper;
code)
 Q. Yao, J. Kwok.
Colorization by PatchBased Local LowRank Matrix Completion.
AAAI Conference on Artificial Intelligence (AAAI).
(paper,
slide)

Others
2020
 Y. Liu, Q. Yao, Y. Li.
Multiary Relational Knowledge Base Completion via Tensor Decomposition.
International Workshop on Tensor Network Representations in Machine Learning@IJCAI.
2020.
 Q. Yao, S. Di, Y. Zhang.
Adaptive Regularizing Tucker Decomposition for Knowledge Graph Completion.
International Workshop on Tensor Network Representations in Machine Learning@IJCAI.
2020.

R. Mehrotra, B. Carterette, Y. Li, Q. Yao, C. Gao, J. Kwok, Q. Yang, I. Guyon.
Advances in Recommender Systems: From Multistakeholder Marketplaces to Automated RecSys.
LectureStyle Tutorials@KDD.
2020.
(slides)
 H. Zhao, L. Wei, Q. Yao.
Simplifying Architecture Search for Graph Neural Network.
1st Workshop Combining Symbolic and Subsymbolic Methods and their Applications@CIKM.
2020.
(paper)
 Y. Zhang, Q. Yao.
Neural Recurrent Structure Search for Knowledge Graph Embedding.
International Workshop on Knowledge Graph@KDD.
2020.
(paper)
2019 and early time
 H. Yang, Q. Yao.
Towards Automated Learning from Noisy Labels.
Asian Conference on Machine Learning: Weaklysupervised Learning Workshop (WSL@ACML).
2019.
(best paper award)
 Q. Yao, M. Wang, Y. Li, W. Tu, Q. Yang, Y. Yu.
Taking Human out of Learning Applications: A Survey on Automated Machine Learning.
Arvix. Nov. 2018.
(the draft is kept updating; any comments and suggestions are welcome)

Z. Liu,
O. Bousquet
A. Elisseeff,
S. Escalera,
I. Guyon,
J. Jacques Jr.,
A. Pavao,
D. Silver,
L. Sun,
S. Treguer,
W. Tu,
J. Wang,
Q. Yao.
AutoDL Challenge Design and Beta Tests  Towards automatic deep learning.
Metalearning workshop@NeurIPS2018.
2018.
(paper)

Q. Yao, J. Kwok, X. Guo.
Fast Learning with Nonconvex L12 Regularization.
ArXiv. Oct. 2016.
(paper)
