Yuheng Bu

Laura Toni

IEEE Trans. Inf. Theory, January, 2024

Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions.

[BibT_eX]

[DOI]

CoRR, 2024

Operator SVD with Neural Networks via Nested Low-Rank Approximation.

[BibT_eX]

[DOI]

CoRR, 2024

Adaptive Text Watermark for Large Language Models.

[BibT_eX]

[DOI]

Yepeng Liu

CoRR, 2024

Class-wise Generalization Error: an Information-Theoretic Analysis.

[BibT_eX]

[DOI]

Firas Laakom

Moncef Gabbouj

CoRR, 2024

2023

SGLD-Based Information Criteria and the Over-Parameterized Regime.

[BibT_eX]

[DOI]

Haobo Chen

CoRR, 2023

Feature Learning in Image Hierarchies using Functional Maximal Correlation.

[BibT_eX]

[DOI]

Bo Hu

José C. Príncipe

CoRR, 2023

Group Fairness with Uncertainty in Sensitive Attributes.

[BibT_eX]

[DOI]

CoRR, 2023

A Bilateral Bound on the Mean-Square Error for Estimation in Model Mismatch.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2023

On the Generalization Error of Meta Learning for the Gibbs Algorithm.

[BibT_eX]

[DOI]

Harsha Vardhan Tetali

Proceedings of the IEEE International Symposium on Information Theory, 2023

On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation.

[BibT_eX]

[DOI]

Maohao Shen

Proceedings of the International Conference on Machine Learning, 2023

Reliable Gradient-free and Likelihood-free Prompt Tuning.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?

[BibT_eX]

[DOI]

Haiyun He

Vincent Y. F. Tan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Maximal Correlation Framework for Fair Machine Learning.

[BibT_eX]

[DOI]

Rogério Schmidt Feris

Entropy, 2022

On the Benefits of Selectivity in Pseudo-Labeling for Unsupervised Multi-Source-Free Domain Adaptation.

[BibT_eX]

[DOI]

Maohao Shen

CoRR, 2022

Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation.

[BibT_eX]

[DOI]

Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Tighter Expected Generalization Error Bounds via Convexity of Information Measures.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2022

Selective Regression under Fairness Criteria.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

A Maximal Correlation Approach to Imposing Fairness in Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2022

Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Population Risk Improvement with Model Compression: An Information-Theoretic Approach.

[BibT_eX]

[DOI]

Weihao Gao

Entropy, 2021

Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information.

[BibT_eX]

[DOI]

Laura Toni

CoRR, 2021

An Exact Characterization of the Generalization Error for the Gibbs Algorithm.

[BibT_eX]

[DOI]

Laura Toni

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SDP Methods for Sensitivity-Constrained Privacy Funnel and Information Bottleneck Problems.

[BibT_eX]

[DOI]

Tony Wang

Proceedings of the IEEE International Symposium on Information Theory, 2021

Fair Selective Classification Via Sufficiency.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Tightening Mutual Information-Based Bounds on Generalization Error.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2020

Information-Theoretic Understanding of Population Risk Improvement with Model Compression.

[BibT_eX]

[DOI]

Weihao Gao

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Information-theoretic bounds in learning algorithms

[BibT_eX]

[DOI]

PhD thesis, 2019

Linear-Complexity Exponentially-Consistent Tests for Universal Outlying Sequence Detection.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Adaptive Sequential Machine Learning.

[BibT_eX]

[DOI]

Craig Wilson

CoRR, 2019

Model Change Detection with Application to Machine Learning.

[BibT_eX]

[DOI]

Jiaxun Lu

Proceedings of the IEEE International Conference on Acoustics, 2019

Active and Adaptive Sequential Learning with Per Time-step Excess Risk Guarantees.

[BibT_eX]

[DOI]

Jiaxun Lu

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Estimation of KL Divergence: Optimal Minimax Rate.

[BibT_eX]

[DOI]

Yingbin Liang

IEEE Trans. Inf. Theory, 2018

Active Learning in Recommendation Systems with Multi-level User Preferences.

[BibT_eX]

[DOI]

Kevin Small

CoRR, 2018

Active and Adaptive Sequential learning.

[BibT_eX]

[DOI]

Jiaxun Lu

CoRR, 2018

2017

Linear Complexity Exponentially Consistent Tests for Outlying Sequence Detection.

[BibT_eX]

[DOI]

CoRR, 2017

2016

Estimation of KL divergence between large-alphabet distributions.

[BibT_eX]

[DOI]

Yingbin Liang

Proceedings of the IEEE International Symposium on Information Theory, 2016

Universal outlying sequence detection for continuous observations.

[BibT_eX]

[DOI]

Yingbin Liang