IEEE BITS the Information Theory Magazine最新文献_第4页

IEEE BITS the Information Theory Magazine Pub Date : 2021-08-01 DOI: 10.1109/mbits.2021.3097878

R. Gallager

{"title":"Shannon, Euler, and Mazes","authors":"R. Gallager","doi":"10.1109/mbits.2021.3097878","DOIUrl":"https://doi.org/10.1109/mbits.2021.3097878","url":null,"abstract":"One of Claude Shannon’s best remembered “toys” was his maze-solving machine, created by partitions on a rectangular grid. A mechanical mouse was started at one point in the maze with the task of finding cheese at another point. Relays under the board guided successive moves, each of which were taken in the first open counterclockwise direction from the previous move. In belated honor of Shannon’s centenary and of amnesia in the mouse at age 70, we compare this deterministic search strategy with a random search requiring no memory. For simplicity, the rectangular grid with partitions is replaced by a finite connected graph. A maze is then a graph with some given destination node. The worst case required number of steps to find the cheese for deterministic searches and the expected number for random searches are remarkably similar, each being, for example, $|mathcal {E}^2|$|E2| taken over all graphs of $|mathcal {E}|$|E| edges. Finally, we demonstrate a simple improvement to the above algorithms that generates an Eulerian cycle on the directed edges of $G$G, i.e., a walk on $G$G of $2|mathcal {E}|$2|E| steps that traverses each edge in $G$G exactly once in each direction before returning to the starting point.","PeriodicalId":448036,"journal":{"name":"IEEE BITS the Information Theory Magazine","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128784340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey on Statistical, Information, and Estimation—Theoretic Views on Privacy 关于隐私的统计、信息和估计理论观点综述

IEEE BITS the Information Theory Magazine Pub Date : 2021-08-01 DOI: 10.1109/MBITS.2021.3108124

Hsiang Hsu, Natalia Martínez, M. Bertrán, Guillermo Sapiro, F. Calmon

{"title":"A Survey on Statistical, Information, and Estimation—Theoretic Views on Privacy","authors":"Hsiang Hsu, Natalia Martínez, M. Bertrán, Guillermo Sapiro, F. Calmon","doi":"10.1109/MBITS.2021.3108124","DOIUrl":"https://doi.org/10.1109/MBITS.2021.3108124","url":null,"abstract":"Privacy has become an emerging challenge in both information theory and computer science due to massive (centralized) collection of user data. In this article, we overview privacy-preserving mechanisms and metrics from the lenses of information theory, and unify different privacy metrics, including f-divergences, Rényi divergences, and differential privacy (DP), in terms of the probability likelihood ratio (and its logarithm). We review recent progress on the design of privacy-preserving mechanisms according to the privacy metrics in computer science, where DP is the standard privacy notion which controls the output shift given small input perturbation, and information theory, where the privacy is guaranteed by minimizing information leakage. In particular, for DP, we include its important variants (e.g., Rényi DP, Pufferfish privacy) and properties, discuss its connections with information-theoretic quantities, and provide the operational interpretations of its additive noise mechanisms. For information-theoretic privacy, we cover notable frameworks, including the privacy funnel, originated from rate-distortion theory and information bottleneck, to privacy guarantee against statistical inference/guessing, and information obfuscation on samples and features. Finally, we discuss the implementations of these privacy-preserving mechanisms in current data-driven machine learning scenarios, including deep learning, information obfuscation, federated learning, and dataset sharing.","PeriodicalId":448036,"journal":{"name":"IEEE BITS the Information Theory Magazine","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115434439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

IEEE Signal Processing Magazine IEEE信号处理杂志

IEEE BITS the Information Theory Magazine Pub Date : 2021-08-01 DOI: 10.1109/mbits.2021.3116479

引用次数: 0

Machine-Proving of Entropy Inequalities 熵不等式的机器证明

IEEE BITS the Information Theory Magazine Pub Date : 2021-08-01 DOI: 10.1109/mbits.2021.3123197

R. Yeung, Cheuk Ting Li

引用次数: 7

6G: The Personal Tactile Internet—And Open Questions for Information Theory 6G:个人触觉互联网——信息理论的开放性问题

IEEE BITS the Information Theory Magazine Pub Date : 2021-08-01 DOI: 10.1109/mbits.2021.3118662

G. Fettweis, H. Boche

引用次数: 52

Joy Thomas: Legacy, Foundation and the IT Society Joy Thomas:遗产、基金会和IT社会

IEEE BITS the Information Theory Magazine Pub Date : 2021-08-01 DOI: 10.1109/mbits.2021.3108946

S. Diggavi, A. Gamal, I. Kontoyiannis, A. Paranjpe, Murali Subbarao

引用次数: 0

THE INFORMATION THEORY SOCIETY PRESENTS 信息论社会呈现

IEEE BITS the Information Theory Magazine Pub Date : 2021-08-01 DOI: 10.1109/mbits.2021.3102337

引用次数: 0

Compressed Ultrasound Imaging: From Sub-Nyquist Rates to Super Resolution 压缩超声成像:从亚奈奎斯特速率到超分辨率

IEEE BITS the Information Theory Magazine Pub Date : 2021-07-23 DOI: 10.1109/mbits.2021.3103144

O. Drori, Alon Mamistvalov, Oren Solomon, Yonina C. Eldar

引用次数: 2

Publications of Information Theory Society 信息理论学会刊物

IEEE BITS the Information Theory Magazine Pub Date : 1900-01-01 DOI: 10.1109/mbits.2021.3111537

Wei-ZhouLuandShun-Zheng Yu

引用次数: 0

Q&A: Meir Feder on Using Information Theory's Concepts to Solve Complex Problems Across Disciplines 问答:Meir Feder关于使用信息论的概念来解决跨学科的复杂问题

IEEE BITS the Information Theory Magazine Pub Date : 1900-01-01 DOI: 10.1109/mbits.2023.3263813

U. Thomas, M. Feder

引用次数: 0