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Yuheng Bu
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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
1852020
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
792018
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
47*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
252016
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
232019
On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
M Shen, Y Bu, G Wornell
International Conference on Machine Learning, 2023
22*2023
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
19*2022
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
172020
Population risk improvement with model compression: An information-theoretic approach
Y Bu, W Gao, S Zou, VV Veeravalli
Entropy 23 (10), 1255, 2021
142021
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
132022
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
122022
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
122016
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
11*2023
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
112022
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
82023
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
72022
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
72019
Active Learning in Recommendation Systems with Multi-level User Preferences
Y Bu, K Small
arXiv preprint arXiv: 1811.12591, 2018
72018
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
62022
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