Information Theory

Function-space regularized Rényi divergences ICLR 2023 Fundamental Tradeoffs in Learning with Prior Information ICML 2023 Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels JMLR 2023 How Does Information Bottleneck Help Deep Learning? ICML 2023 How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm? AISTATS 2023 Information Theoretic Lower Bounds for Information Theoretic Upper Bounds NeurIPS 2023 JacobiNeRF: NeRF Shaping With Mutual Information Gradients CVPR 2023 Label Information Bottleneck for Label Enhancement CVPR 2023 Measuring Pointwise 𝒱-Usable Information In-Context-ly EMNLP 2023 Minimum Description Length and Generalization Guarantees for Representation Learning NeurIPS 2023 Norm of Word Embedding Encodes Information Gain EMNLP 2023 On Slicing Optimality for Mutual Information NeurIPS 2023 Parametric Information Maximization for Generalized Category Discovery ICCV 2023 Prediction-Oriented Bayesian Active Learning AISTATS 2023 Prototypical Model with Information-Theoretic Loss Functions for Generalized Zero-Shot Learning ACML 2023 Recognizable Information Bottleneck IJCAI 2023 Revisiting Entropy Rate Constancy in Text EMNLP 2023 Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds NeurIPS 2023 Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints COLT 2023 Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training EMNLP 2023 The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization AAAI 2023 Tighter Information-Theoretic Generalization Bounds from Supersamples ICML 2023 Tokenization and the Noiseless Channel ACL 2023 Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning EMNLP 2023 Towards Stable Natural Language Understanding via Information Entropy Guided Debiasing ACL 2023