← Optimization & Theory
Machine Learning › Optimization & Theory ›

Information Theory

313 directly classified papers

Papers per year

Papers

Gibbs-Based Information Criteria and the Over-Parameterized Regime AISTATS 2024
Information-theoretic Generalization Analysis for Expected Calibration Error NIPS 2024
Towards Explainable Joint Models via Information Theory for Multiple Intent Detection and Slot Filling AAAI 2024
An Information-Theoretic Approach to Analyze NLP Classification Tasks ACL 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures AISTATS 2024
Revisiting the Information Capacity of Neural Network Watermarks: Upper Bound Estimation and Beyond AAAI 2024
Learning to Write Rationally: How Information Is Distributed in Non-native Speakers’ Essays EMNLP 2024
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data NIPS 2024
Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method EMNLP 2024
Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models NIPS 2024
Accelerating Relative Entropy Coding with Space Partitioning NIPS 2024
Information Capacity Regret Bounds for Bandits with Mediator Feedback JMLR 2024
Enhancing Evolving Domain Generalization through Dynamic Latent Representations AAAI 2024
Efficiently Computing Susceptibility to Context in Language Models EMNLP 2024
Universal Exact Compression of Differentially Private Mechanisms NIPS 2024
DIET: Conditional independence testing with marginal dependence measures of residual information AISTATS 2023
Diffeomorphic Information Neural Estimation AAAI 2023
A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decomposition JMLR 2023
Recognizable Information Bottleneck IJCAI 2023
An Information-Theoretic Analysis of Self-supervised Discrete Representations of Speech INTERSPEECH 2023
The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization AAAI 2023
Tokenization and the Noiseless Channel ACL 2023
How Does Information Bottleneck Help Deep Learning? ICML 2023
Parametric Information Maximization for Generalized Category Discovery ICCV 2023
Fundamental Tradeoffs in Learning with Prior Information ICML 2023