| Tightening mutual information-based bounds on generalization error Y Bu, S Zou, VV Veeravalli IEEE Journal on Selected Areas in Information Theory 1 (1), 121-130, 2020 | 181 | 2020 |
| Estimation of KL Divergence: Optimal Minimax Rate Y Bu, S Zou, Y Liang, V Veeravalli IEEE Transactions on Information Theory 64 (4), 2648-2674, 2018 | 75 | 2018 |
| An exact characterization of the generalization error for the Gibbs algorithm G Aminian, Y Bu, L Toni, M Rodrigues, G Wornell Advances in Neural Information Processing Systems 34, 8106-8118, 2021 | 45* | 2021 |
| Estimation of KL divergence between large-alphabet distributions Y Bu, S Zou, Y Liang, VV Veeravalli 2016 IEEE International Symposium on Information Theory (ISIT), 1118-1122, 2016 | 24 | 2016 |
| Fair selective classification via sufficiency JK Lee, Y Bu, D Rajan, P Sattigeri, R Panda, S Das, GW Wornell International conference on machine learning, 6076-6086, 2021 | 23* | 2021 |
| Linear-complexity exponentially-consistent tests for universal outlying sequence detection Y Bu, S Zou, V Veeravalli IEEE Transactions on Signal Processing, 2019 | 21 | 2019 |
| On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation M Shen, Y Bu, G Wornell International Conference on Machine Learning, 2023 | 20* | 2023 |
| Information-theoretic understanding of population risk improvement with model compression Y Bu, W Gao, S Zou, V Veeravalli Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3300-3307, 2020 | 17 | 2020 |
| Selective regression under fairness criteria A Shah, Y Bu, JK Lee, S Das, R Panda, P Sattigeri, GW Wornell International Conference on Machine Learning, 19598-19615, 2022 | 16* | 2022 |
| Tighter expected generalization error bounds via convexity of information measures G Aminian, Y Bu, GW Wornell, MRD Rodrigues 2022 IEEE International Symposium on Information Theory (ISIT), 2481-2486, 2022 | 13 | 2022 |
| Population risk improvement with model compression: An information-theoretic approach Y Bu, W Gao, S Zou, VV Veeravalli Entropy 23 (10), 1255, 2021 | 13 | 2021 |
| Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm Y Bu, G Aminian, L Toni, GW Wornell, M Rodrigues International Conference on Artificial Intelligence and Statistics, 8673-8699, 2022 | 12 | 2022 |
| Universal outlying sequence detection for continuous observations Y Bu, S Zou, Y Liang, VV Veeravalli 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 11 | 2016 |
| A maximal correlation approach to imposing fairness in machine learning J Lee, Y Bu, P Sattigeri, R Panda, G Wornell, L Karlinsky, R Feris ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 10 | 2022 |
| Post-hoc Uncertainty Learning using a Dirichlet Meta-Model M Shen, Y Bu, P Sattigeri, S Ghosh, S Das, G Wornell Proceedings of the AAAI Conference on Artificial Intelligence, 2023 | 8* | 2023 |
| Model change detection with application to machine learning Y Bu, J Lu, VV Veeravalli ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 7 | 2019 |
| Active Learning in Recommendation Systems with Multi-level User Preferences Y Bu, K Small arXiv preprint arXiv: 1811.12591, 2018 | 7 | 2018 |
| Information-theoretic characterizations of generalization error for the Gibbs algorithm G Aminian, Y Bu, L Toni, MRD Rodrigues, GW Wornell IEEE Transactions on Information Theory, 2023 | 6 | 2023 |
| Data-driven blind synchronization and interference rejection for digital communication signals A Lancho, A Weiss, GCF Lee, J Tang, Y Bu, Y Polyanskiy, GW Wornell GLOBECOM 2022-2022 IEEE Global Communications Conference, 2296-2302, 2022 | 6 | 2022 |
| A maximal correlation framework for fair machine learning J Lee, Y Bu, P Sattigeri, R Panda, GW Wornell, L Karlinsky, ... Entropy 24 (4), 461, 2022 | 6 | 2022 |
Gregory WornellProfessor, Electrical Engineering and Computer Science, MITVerified email at mit.edu
