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"Bounds on information combining" are entropic inequalities that determine how the information (entropy) of a set of random variables can change when these are combined in certain prescribed ways. Such bounds play an important role in…

Quantum Physics · Physics 2019-08-27 Christoph Hirche , David Reeb

We identify the common underlying form of the capacity expression that is applicable to both cases where causal or non-causal side information is made available to the transmitter. Using this common form we find that for the single user…

Information Theory · Computer Science 2007-07-13 Syed A. Jafar

We focus our attention on the most common scenario in networked control systems where the measured output from the observer is transmitted via a communication channel to the controller. Using information theoretic results, we studied the…

Systems and Control · Computer Science 2019-06-24 Ayush Pandey

Several studies have identified a significant amount of redundancy in the network traffic. For example, it is demonstrated that there is a great amount of redundancy within the content of a server over time. This redundancy can be leveraged…

Information Theory · Computer Science 2016-11-18 Mohsen Sardari , Ahmad Beirami , Faramarz Fekri

Code concatenation combines two or more component codes to design larger codes with greater noise resilience. Introducing entanglement assistance to concatenated codes provides a further advantage in terms of improved error rates and…

Quantum Physics · Physics 2025-11-25 Nihar Ranjan Dash , Sanjoy Dutta , R. Srikanth , Subhashish Banerjee

We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections, a problem relevant in compressed sensing, sparse superposition codes or code division multiple access just to cite few. There has…

Information Theory · Computer Science 2017-03-24 Jean Barbier , Mohamad Dia , Nicolas Macris , Florent Krzakala

This paper investigates the asymptotic expansion for the maximum rate of fixed-length codes over a parallel Gaussian channel with feedback under the following setting: A peak power constraint is imposed on every transmitted codeword, and…

Information Theory · Computer Science 2017-07-11 Silas L. Fong , Vincent Y. F. Tan

Region-of-Interest (ROI)-based image compression allocates bits unevenly according to the semantic importance of different regions. Such differentiated coding typically induces a sharp-peaked and heavy-tailed distribution. This distribution…

Image and Video Processing · Electrical Eng. & Systems 2026-02-03 Kai Hu , Junfu Tan , Fang Xu , Ramy Samy , Yu Liu

We study a two-user state-dependent generalized multiple-access channel (GMAC) with correlated states. It is assumed that each encoder has \emph{noncausal} access to channel state information (CSI). We develop an achievable rate region by…

Information Theory · Computer Science 2014-09-09 Mohammad Javad Emadi , Majid Nasiri Khormuji , Mikael Skoglund , Mohammad Reza Aref

A two-user discrete memoryless compound multiple access channel with a common message and conferencing decoders is considered. The capacity region is characterized in the special cases of physically degraded channels and unidirectional…

Information Theory · Computer Science 2016-11-18 O. Simeone , D. Gunduz , H. V. Poor , A. Goldsmith , S. Shamai

We tackle the problem of collaborative filtering (CF) with side information, through the lens of Gaussian Process (GP) regression. Driven by the idea of using the kernel to explicitly model user-item similarities, we formulate the GP in a…

Machine Learning · Statistics 2017-06-09 Hyunjik Kim , Xiaoyu Lu , Seth Flaxman , Yee Whye Teh

To alleviate data sparsity and cold-start problems of traditional recommender systems (RSs), incorporating knowledge graphs (KGs) to supplement auxiliary information has attracted considerable attention recently. However, simply integrating…

Information Retrieval · Computer Science 2022-01-04 Yankai Chen , Yaming Yang , Yujing Wang , Jing Bai , Xiangchen Song , Irwin King

Variational autoencoders optimize an objective that combines a reconstruction loss (the distortion) and a KL term (the rate). The rate is an upper bound on the mutual information, which is often interpreted as a regularizer that controls…

Generalization error bounds are essential to understanding machine learning algorithms. This paper presents novel expected generalization error upper bounds based on the average joint distribution between the output hypothesis and each…

Information Theory · Computer Science 2022-02-25 Gholamali Aminian , Yuheng Bu , Gregory Wornell , Miguel Rodrigues

We consider a backhaul-constrained coordinated cellular network. That is, a single-frequency network with $N+1$ multi-antenna base stations (BSs) that cooperate in order to decode the users' data, and that are linked by means of a common…

Information Theory · Computer Science 2008-02-07 Aitor del Coso , Sebastien Simoens

We introduce a new protocol for a lossy data compression algorithm which is based on constraint satisfaction gates. We show that the theoretical capacity of algorithms built from standard parity-check gates converges exponentially fast to…

Disordered Systems and Neural Networks · Physics 2009-11-11 S. Ciliberti , M. Mezard , R. Zecchina

We propose a covert communication protocol for the spread-spectrum multiple random access with additive white Gaussian noise (AWGN) channel. No existing paper has studied covert communication for the random access channel. Our protocol…

Information Theory · Computer Science 2023-10-25 Masahito Hayashi , Angeles Vazquez-Castro

Simultaneous transmission of information and power over a point-to-point flat-fading complex Additive White Gaussian Noise (AWGN) channel is studied. In contrast with the literature that relies on an inaccurate linear model of the energy…

Information Theory · Computer Science 2017-06-01 Morteza Varasteh , Borzoo Rassouli , Bruno Clerckx

Round-based models are very common message-passing models; combinatorial topology applied to distributed computing provides sweeping results like general lower bounds. We combine both to study the computability of k-set agreement. Among all…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-15 Adam Shimi , Armando Castañeda

Neural network models have shown outstanding performance and successful resolutions to complex problems in various fields. However, the majority of these models are viewed as black-box, requiring a significant amount of data for…

Machine Learning · Computer Science 2024-04-04 Wanli Xie , Ruibin Zhao , Zhenguo Xu , Tingting Liang
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