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Research

My current research interest:

• Imitation Learning

• Weakly-supervised Learning

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Selected Recent Publications

• X. Yu, Y. Lyu and I.W. Tsang. Intrinsic Reward Driven Imitation Learning via Generative Model. In International Conference on Machine Learning, 2020, [PDF][Code][Slides][WebPage].

• X. Yu, B. Han, J. Yao, G. Niu, I.W. Tsang and M. Sugiyama. How does disagreement help generalization against label corruption? In International Conference on Machine Learning, 2019, [PDF][Code].

• B. Han, Q. Yao, X. Yu, G. Niu, M. Xu, W. Hu, I.W. Tsang and M. Sugiyama. Co-teaching: Robust training of deep neural networks with extremely noisy labels. In Advances in Neural Information Processing Systems, 2018, [PDF][Code].

• X. Yu, H. Zhang, C. Luo, H. Qi and P. Ren. Oil spill segmentation via adversarial f-divergence learning. IEEE Transactions on Geoscience and Remote Sensing, 56(9): 4973-4988, 2018, [PDF][Code].

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Professional Service

• Conference Reviewer/Program Committee:

• NeurIPS-2019, ACML-2019

• AAAI-2020, ICML-2020, IJCAI-PRICAI-2020, NeurIPS-2020, ACML-2020

• ICLR-2021

• Journal Reviewer:

• IEEE TPAMI

• Machine Learning

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Awards

• ICML-2019 Travel Award

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Brief Biography

Xingrui Yu is currently a second-year Ph.D. student at Australian Artificial Intelligence Institute in University of Technology Sydney(UTS), supervised by Prof. Ivor W. Tsang. Before that, he received his B.Eng degree in Electronic Information Enginering and M.Eng degree in Information and Communication Engineering from China University of Petroleum (East China) in 2015 and 2018, respectively.