| Curriculum Loss: Robust Learning and Generalization against Label Corruption Y Lyu, IW Tsang The International Conference on Learning Representations (ICLR), 2019 | 195 | 2019 |
| Marginalized average attentional network for weakly-supervised learning Y Yuan, Y Lyu, X Shen, IW Tsang, DY Yeung The International Conference on Learning Representations (ICLR), 2019 | 104 | 2019 |
| Intrinsic Reward Driven Imitation Learning via Generative Model X Yu, Y Lyu, IW Tsang International Conference on Machine Learning (ICML), 2020 | 53 | 2020 |
| Asymmetric cyclical hashing for large scale image retrieval Y Lv, WWY Ng, Z Zeng, DS Yeung, PPK Chan IEEE Transactions on Multimedia 17 (8), 1225-1235, 2015 | 49 | 2015 |
| Spherical structured feature maps for kernel approximation Y Lyu International Conference on Machine Learning (ICML), 2017 | 30 | 2017 |
| Incremental hashing for semantic image retrieval in nonstationary environments WWY Ng, X Tian, Y Lv, DS Yeung, W Pedrycz IEEE transactions on cybernetics 47 (11), 3814-3826, 2016 | 30 | 2016 |
| Two-phase mapping hashing WWY Ng, Y Lv, DS Yeung, PPK Chan Neurocomputing 151, 1423-1429, 2015 | 15 | 2015 |
| Sequential conditional entropy maximization semi-supervised hashing for semantic image retrieval WWY Ng, Y Lv, Z Zeng, DS Yeung, PPK Chan International Journal of Machine Learning and Cybernetics 8, 571-586, 2017 | 12 | 2017 |
| Efficient batch black-box optimization with deterministic regret bounds Y Lyu, Y Yuan, IW Tsang arXiv preprint arXiv:1905.10041, 2019 | 11 | 2019 |
| Black-box Optimizer with Implicit Natural Gradient Y Lyu, IW Tsang arXiv preprint arXiv:1910.04301, 2019 | 9* | 2019 |
| Subgroup-based Rank-1 Lattice Quasi-Monte Carlo Y Lyu, Y Yuan, IW Tsang Neural Information Processing Systems (NeurIPS), 2020 | 7 | 2020 |
| On harmonizing implicit subpopulations F Hong, J Yao, Y Lyu, Z Zhou, I Tsang, Y Zhang, Y Wang The Twelfth International Conference on Learning Representations, 2024 | 5 | 2024 |
| Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning F Ye, Y Lyu, X Wang, Y Zhang, I Tsang The Twelfth International Conference on Learning Representations, 2024 | 5* | 2024 |
| Online mental fatigue monitoring via indirect brain dynamics evaluation Y Pan, IW Tsang, Y Lyu, AK Singh, CT Lin Neural Computation 33 (6), 1616-1655, 2021 | 5 | 2021 |
| Earning extra performance from restrictive feedbacks J Li, Y Pan, Y Lyu, Y Yao, Y Sui, IW Tsang IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (10 …, 2023 | 3 | 2023 |
| A cone order sequence based multi-objective evolutionary algorithm Y Lyu, Q Zhang, KC Wong 2016 IEEE Congress on Evolutionary Computation (CEC), 2169-2176, 2016 | 3 | 2016 |
| Hyperspherical embedding iterative quantization hashing Z Huang, Y Lv, X Tian, WWY Ng 2015 International Conference on Machine Learning and Cybernetics 2, 904-909, 2015 | 3 | 2015 |
| Diversified Batch Selection for Training Acceleration F Hong, Y Lyu, J Yao, Y Zhang, IW Tsang, Y Wang The Forty-first International Conference on Machine Learning (ICML 2024), 2024 | 2 | 2024 |
| Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search KY Tan, Y Lyu, YS Ong, IW Tsang arXiv preprint arXiv:2304.02350, 2023 | 2 | 2023 |
| Fast rank-1 lattice targeted sampling for black-box optimization Y Lyu Advances in Neural Information Processing Systems 36, 2023 | 2 | 2023 |
Ivor W. Tsang, IEEE FellowInaugural A*STAR AI Fellow and Director, Centre for Frontier AI Research, A*STARVerified email at cfar.a-star.edu.sg
