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Representative works   

  • Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML-2020
  • Efficient Neural Interaction Functions Search for Collaborative Filtering. WebConf-2020
  • Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers. TPAMI-2019
  • Efficient Learning with Nonconvex Regularizers by Nonconvexity Redistribution. JMLR-2018
  • Co-teaching: Robust training deep neural networks with extremely noisy labels. NeurIPS-2018

Publications

2020
  • W. He, Q. Yao, C. Li, N. Yokoya, Q. Zhao, H. Zhang, L. Zhang. Non-local 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 Few-Shot Learning. ACM Computing Surveys (CSUR). (paper, update-to-date 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 N-ary 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 Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. IEEE International Conference on Data Engineering (ICDE). (paper)
2019
  • Q. Yao, J. Kwok, T. Wang, T. Liu. Large-Scale Low-Rank 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 Soft-Impute for Large-Scale 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 Side-information by Semi-definite 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. State-Sharing 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 Real-World 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 Structure-aware 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. Non-local 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) [Top-10 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 Hint-guided 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. Co-teaching: Robust training deep neural networks with extremely noisy labels. Advance in Neural Information Processing Systems (NeurIPS). (paper, slides; code) [Top-15 cited paper in NeurIPS 2018]
  • Y. Wang, Q. Yao, J. Kwok, L. Ni. Online Convolutional Sparse Coding with Sample-Dependent 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. Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). (paper; code) [Top-15 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. Loss-aware Binarization of Deep Networks. International Conference on Learning Representations (ICLR). (paper; code)
  • Y. Wang, J. Kwok, Q. Yao, L. Ni. Zero-Shot Learning with a Partial Set of Observed Attributes. International Joint Conference on Neural Networks (IJCNN). (paper)
  • X. Guo, Q. Yao, J. Kwok. Efficient Sparse Low-Rank Tensor Completion using Frank-Wolfe 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 Low-Rank Models. International Joint Conference on Artificial Intelligence (IJCAI). (paper, appendix)
2015
  • Q. Yao, J. Kwok, W. Zhong. Fast Low-Rank Matrix Learning with Nonconvex Regularization. IEEE International Conference on Data Mining (ICDM). (paper, slide; code)
  • Q. Yao, J. Kwok. Accelerated Inexact Soft-Impute for Fast Large-Scale Matrix Completion. International Joint Conference on Artificial Intelligence (IJCAI). (paper; code)
  • Q. Yao, J. Kwok. Colorization by Patch-Based Local Low-Rank 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 Multi-stakeholder Marketplaces to Automated RecSys. Lecture-Style 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: Weakly-supervised 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. Meta-learning workshop@NeurIPS-2018. 2018. (paper)
  • Q. Yao, J. Kwok, X. Guo. Fast Learning with Nonconvex L1-2 Regularization. ArXiv. Oct. 2016. (paper)