2019 IEEE International Symposium on Information Theory (ISIT)最新文献_第9页

Secure Broadcasting of Two Encrypted Sources under Side-Channel Attacks 侧信道攻击下两个加密源的安全广播

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849849

Bagus Santoso, Y. Oohama

引用次数: 0

Robust Gradient Descent via Moment Encoding and LDPC Codes 基于矩编码和LDPC码的鲁棒梯度下降

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849514

R. Maity, A. Rawat, A. Mazumdar

引用次数: 31

A Unified Adaptive Recoding Framework for Batched Network Coding 批处理网络编码的统一自适应重编码框架

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849277

Hoover H. F. Yin, Bin Tang, Ka Hei Ng, Shenghao Yang, Xishi Wang, Qiaoqiao Zhou

{"title":"A Unified Adaptive Recoding Framework for Batched Network Coding","authors":"Hoover H. F. Yin, Bin Tang, Ka Hei Ng, Shenghao Yang, Xishi Wang, Qiaoqiao Zhou","doi":"10.1109/ISIT.2019.8849277","DOIUrl":"https://doi.org/10.1109/ISIT.2019.8849277","url":null,"abstract":"Batched network coding is a variation of random linear network coding which has low computational and storage costs. In order to adapt random fluctuations in the number of erasures in individual batches, it is not optimal to recode and transmit the same number of packets for all batches. Different distributed optimization problems, which are called adaptive recoding, were formulated for this purpose. The key component of these optimization problems is the expected value of the rank distribution of a batch at the next network node, which also known as the expected rank. In this paper, we put forth a unified adaptive recoding framework. We show that the expected rank functions are concave when the packet loss pattern follows a stationary stochastic process regardless of the field size, which covers but not limited to independent packet loss and burst packet loss. Under this concavity property, we show that there always exists a preferred solution which not only can make the number of recoded packets almost deterministic but can also tolerate rank distribution errors due to inaccurate measurements or limited precision of the machine. To obtain such an optimal solution, we propose tuning schemes that can turn any feasible solution into one with the above desired properties.","PeriodicalId":6708,"journal":{"name":"2019 IEEE International Symposium on Information Theory (ISIT)","volume":"35 1","pages":"1962-1966"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81965798","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: 2

The Exact Capacity-Memory Tradeoff for Caching with Uncoded Prefetching in the Two-Receiver Gaussian Broadcast Channel 双接收机高斯广播信道中非编码预取缓存的准确容量-内存权衡

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849343

M. Salman, M. Varanasi

引用次数: 3

Privacy Amplification, Lossy Compression, and their Duality to Channel Coding 隐私放大、有损压缩及其对信道编码的对偶性

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849490

J. Renes

{"title":"Privacy Amplification, Lossy Compression, and their Duality to Channel Coding","authors":"J. Renes","doi":"10.1109/ISIT.2019.8849490","DOIUrl":"https://doi.org/10.1109/ISIT.2019.8849490","url":null,"abstract":"We examine the task of privacy amplification from information-theoretic and coding-theoretic points of view. In the former, we give a one-shot characterization of the optimal rate of privacy amplification against classical adversaries in terms of the optimal type-II error in asymmetric hypothesis testing. This formulation can be easily computed to give finite- blocklength bounds and turns out to be equivalent to smooth min-entropy bounds by Renner and Wolf [Asiacrypt 2005] and Watanabe and Hayashi [ISIT 2013], as well as a bound in terms of the Eγ divergence by Yang, Schaefer, and Poor [arXiv:1706.03866 [cs.IT]]. In the latter, we show that protocols for privacy amplification based on linear codes can be easily repurposed for lossy compression. Our construction leads to protocols of optimal rate in the asymptotic i.i.d. limit for a variety of compression scenarios. Finally, appealing to the notion of channel duality recently detailed by us in [IEEE Trans. Inf. Theory 64,577 (2018)], we show that linear error-correcting codes for symmetric channels with quantum output can be transformed into linear lossy source coding schemes for classical variables arising from the dual channel. This explains a “curious duality” in these problems for the (self-dual) erasure channel observed by Martinian and Yedidia [Allerton 2003; arXiv:cs/0408008] and partly anticipates recent results on optimal lossy compression by polar and low-density generator matrix codes.","PeriodicalId":6708,"journal":{"name":"2019 IEEE International Symposium on Information Theory (ISIT)","volume":"33 1","pages":"2144-2148"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85792262","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

Mapping Heterogeneity Does Not Affect Wireless Coded MapReduce 映射异构不影响无线编码MapReduce

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849492

Eleftherios Lampiris, Daniel Jiménez Zorrilla, P. Elia

引用次数: 2

Coded Caching with Heterogeneous File Demand Sets — The Insufficiency of Selfish Coded Caching 异构文件需求集的编码缓存——自私编码缓存的不足

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849357

Chih-Hua Chang, Chih-Chun Wang

{"title":"Coded Caching with Heterogeneous File Demand Sets — The Insufficiency of Selfish Coded Caching","authors":"Chih-Hua Chang, Chih-Chun Wang","doi":"10.1109/ISIT.2019.8849357","DOIUrl":"https://doi.org/10.1109/ISIT.2019.8849357","url":null,"abstract":"This work falls under the broad setting of coded caching with user-dependent file popularity and average-rate capacity analysis. In general, the exact capacity characterization with user-dependent file popularity remains an open problem. For example, user 1 may be interested in files 1 and 2 with probabilities 0.6 and 0.4, respectively, while user 2 may be interested in only files 2, and 3 with probabilities 1/3 and 2/3, respectively, but not interested in file 1 at all. An optimal scheme needs to carefully balance the conflicting interests under the given probabilistic weights. Motivated by this fundamental but intrinsically difficult problem, this work studies the following simplified setting: Each user k is associated with a file demand set (FDS) Θk; each file in Θk is equally desired by user k with probability $frac{1}{{left| {{Theta _k}} right|}}$; and files outside Θk is not desired at all. Different users may have different Θk1 ≠ Θk2, which reflects the user-dependent file popularity. Various capacity results have been derived (mostly for the cases of K = 2 users). One surprising byproduct is a proof showing that selfish coded caching is insufficient to achieve the capacity. That is, in an optimal coded caching scheme, a user sometimes has to cache the files of which he/she has zero interests.","PeriodicalId":6708,"journal":{"name":"2019 IEEE International Symposium on Information Theory (ISIT)","volume":"37 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82191100","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: 18

Information-Theoretic Privacy Watchdogs 信息论隐私监管机构

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849440

Hsiang Hsu, S. Asoodeh, F. Calmon

引用次数: 18

A Graph-Based Modular Coding Scheme Which Achieves Semantic Security 一种实现语义安全的基于图的模块化编码方案

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849471

M. Wiese, H. Boche

引用次数: 1

Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation 稀疏噪声张量估计的迭代协同滤波

2019 IEEE International Symposium on Information Theory (ISIT) Pub Date : 2019-07-01 DOI: 10.1109/ISIT.2019.8849683

D. Shah, C. Yu

{"title":"Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation","authors":"D. Shah, C. Yu","doi":"10.1109/ISIT.2019.8849683","DOIUrl":"https://doi.org/10.1109/ISIT.2019.8849683","url":null,"abstract":"We consider the task of tensor estimation, i.e. estimating a low-rank 3-order n × n × n tensor from noisy observations of randomly chosen entries in the sparse regime. In the context of matrix (2-order tensor) estimation, a variety of algorithms have been proposed and analyzed in the literature including the popular collaborative filtering algorithm that is extremely well utilized in practice. However, in the context of tensor estimation, there is limited progress. No natural extensions of collaborative filtering are known beyond \"flattening\" the tensor into a matrix and applying standard collaborative filtering.As the main contribution of this work, we introduce a generalization of the collaborative filtering algorithm for the setting of tensor estimation and argue that it achieves sample complexity that (nearly) matches the conjectured lower bound on the sample complexity. Interestingly, our generalization uses the matrix obtained from the \"flattened\" tensor to compute similarity as in the classical collaborative filtering but by defining a novel \"graph\" using it. The algorithm recovers the tensor with mean-squared-error (MSE) decaying to 0 as long as each entry is observed independently with probability p = Ω(n−3/2+ϵ) for any arbitrarily small ϵ > 0. It turns out that p = Ω(n−3/2) is the conjectured lower bound as well as \"connectivity threshold\" of graph considered to compute similarity in our algorithm.","PeriodicalId":6708,"journal":{"name":"2019 IEEE International Symposium on Information Theory (ISIT)","volume":"27 1","pages":"41-45"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80723438","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