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rate-distortion theory

20 papers

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Co-occurring keywords

information theory (491) information bottleneck (229) neural network compression (114) information-directed sampling (8) regret bound (1926) generalization bound (652) bayesian regret (33) rate distortion (41) sequential decision-making (94) model compression (3302)

Papers

RD-DPP: Rate-Distortion Theory Meets Determinantal Point Process to Diversify Learning Data Samples WACV 2025
Collaborative Rational Speech Act: Pragmatic Reasoning for Multi-Turn Dialog EMNLP 2025
Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models NIPS 2024
Deep Generative Model based Rate-Distortion for Image Downscaling Assessment CVPR 2024
An Information-Theoretic Justification for Model Pruning AISTATS 2022
SoFaiR: Single Shot Fair Representation Learning IJCAI 2022
Domain Generalization without Excess Empirical Risk NIPS 2022
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms COLT 2022
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds AISTATS 2022
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning NIPS 2022
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning NIPS 2022
Regret Bounds for Information-Directed Reinforcement Learning NIPS 2022
Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding ICML 2021
Permute, Quantize, and Fine-Tune: Efficient Compression of Neural Networks CVPR 2021
Deciding What to Learn: A Rate-Distortion Approach ICML 2021
The Value of Information When Deciding What to Learn NIPS 2021
Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization AAAI 2021
Parameterized Rate-Distortion Stochastic Encoder ICML 2020
State Abstraction as Compression in Apprenticeship Learning AAAI 2019
NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing ACL 2018