Tag: information theory
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Calibrated Surprise: Measuring Creative Quality with Info Theory
Explore how calibrated surprise and information theory quantify creative quality in writing, blending author intent, reader expectation, and logic.
AI Information-Theoretic Measures: Practical Selection Guide
Discover a practical guide to selecting the right information-theoretic measures for AI, enhancing decision-making and model accuracy.
Fast, Accurate Approximations of Entropic Measures
Discover fast, non-singular, and property-preserving approximations of entropic measures like Shannon entropy and KL divergence for efficient ML and physic...
Measuring Interaction Efficiency in Deployed Reinforcement Learning
Discover a novel bounded measure to monitor and improve interaction efficiency in deployed reinforcement learning agents for better reliability.
Information-Theoretic Limits of Single-State Ontological Models
Explore the information-theoretic constraints on single-state ontological models and their impact on contextuality in quantum theory and classical represen...