惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

雷峰网
雷峰网
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
T
Tailwind CSS Blog
F
Fortinet All Blogs
Microsoft Azure Blog
Microsoft Azure Blog
Jina AI
Jina AI
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
N
Netflix TechBlog - Medium
B
Blog RSS Feed
Blog — PlanetScale
Blog — PlanetScale
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
T
The Blog of Author Tim Ferriss
D
Docker
博客园 - 聂微东
博客园 - 【当耐特】
博客园 - 三生石上(FineUI控件)
L
LangChain Blog
量子位
宝玉的分享
宝玉的分享
博客园 - 司徒正美
The Cloudflare Blog
G
Google Developers Blog
Microsoft Security Blog
Microsoft Security Blog
腾讯CDC

cs.IT updates on arXiv.org

Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Entropic Isoperimetric and Cramér--Rao Inequalities for R...
Hao Wu, Lei Yu · 2025-04-02 · via cs.IT updates on arXiv.org

The de Bruijn identity states that Fisher information is equal to a half of the time-derivative of Shannon differential entropy along heat flow. In the same spirit, a generalized version of Fisher information, which we term the Rényi--Fisher information, is defined as a half of the time-derivative of Rényi differential entropy along heat flow. Based on this Rényi--Fisher information, we establish several sharp Rényi-entropic isoperimetric inequalities, which generalize the classic entropic isoperimetric inequality to the Rényi setting. Utilizing these isoperimetric inequalities, we extend the classical Cramér--Rao inequality from Fisher information to Rényi--Fisher information. We then use these generalized Cramér--Rao inequalities to determine the signs of derivatives of Rényi entropy along heat flow, strengthening existing results on the complete monotonicity of Rényi entropy. We lastly explore the implications of our Rényi-entropic isoperimetric inequalities for entropy power inequalities. We demonstrate that, unlike in the Shannon entropy case, the classic entropy power inequality does not admit a direct extension to Rényi entropy without introducing additional exponents or scaling factors. Furthermore, we establish a sharp Rényi entropy power inequality involving a scaling factor under the assumption that one of two independent random vectors is Gaussian.