Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

COMPUTER SCIENCE (1305 journals)            First | 1 2 3 4 5 6 7 | Last

Showing 201 - 400 of 872 Journals sorted alphabetically
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 12)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 11)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 1)
Computational Optimization and Applications     Hybrid Journal   (Followers: 9)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 15)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 35)
Computational Toxicology     Hybrid Journal  
Computer     Full-text available via subscription   (Followers: 141)
Computer Aided Surgery     Open Access   (Followers: 5)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Communications     Hybrid Journal   (Followers: 19)
Computer Engineering and Applications Journal     Open Access   (Followers: 8)
Computer Journal     Hybrid Journal   (Followers: 7)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 25)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 10)
Computer Methods in Biomechanics and Biomedical Engineering : Imaging & Visualization     Hybrid Journal  
Computer Music Journal     Hybrid Journal   (Followers: 18)
Computer Physics Communications     Hybrid Journal   (Followers: 9)
Computer Science - Research and Development     Hybrid Journal   (Followers: 7)
Computer Science and Engineering     Open Access   (Followers: 15)
Computer Science and Information Technology     Open Access   (Followers: 12)
Computer Science Education     Hybrid Journal   (Followers: 15)
Computer Science Journal     Open Access   (Followers: 20)
Computer Science Review     Hybrid Journal   (Followers: 12)
Computer Standards & Interfaces     Hybrid Journal   (Followers: 3)
Computer Supported Cooperative Work (CSCW)     Hybrid Journal   (Followers: 8)
Computer-aided Civil and Infrastructure Engineering     Hybrid Journal   (Followers: 9)
Computer-Aided Design and Applications     Hybrid Journal   (Followers: 6)
Computers     Open Access   (Followers: 2)
Computers & Chemical Engineering     Hybrid Journal   (Followers: 12)
Computers & Education     Hybrid Journal   (Followers: 90)
Computers & Electrical Engineering     Hybrid Journal   (Followers: 8)
Computers & Geosciences     Hybrid Journal   (Followers: 30)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 9)
Computers & Structures     Hybrid Journal   (Followers: 43)
Computers & Education Open     Open Access   (Followers: 2)
Computers & Industrial Engineering     Hybrid Journal   (Followers: 6)
Computers and Composition     Hybrid Journal   (Followers: 11)
Computers and Education: Artificial Intelligence     Open Access   (Followers: 2)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 7)
Computers and Geotechnics     Hybrid Journal   (Followers: 12)
Computers in Biology and Medicine     Hybrid Journal   (Followers: 11)
Computers in Entertainment     Hybrid Journal  
Computers in Human Behavior Reports     Open Access  
Computers in Industry     Hybrid Journal   (Followers: 7)
Computers in the Schools     Hybrid Journal   (Followers: 8)
Computers, Environment and Urban Systems     Hybrid Journal   (Followers: 11)
Computerworld Magazine     Free   (Followers: 2)
Computing     Hybrid Journal   (Followers: 2)
Computing and Software for Big Science     Hybrid Journal   (Followers: 1)
Computing and Visualization in Science     Hybrid Journal   (Followers: 6)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 31)
Computing Reviews     Full-text available via subscription   (Followers: 1)
Concurrency and Computation: Practice & Experience     Hybrid Journal  
Connection Science     Hybrid Journal  
Control Engineering Practice     Hybrid Journal   (Followers: 46)
Cryptologia     Hybrid Journal   (Followers: 3)
CSI Transactions on ICT     Hybrid Journal   (Followers: 2)
Cuadernos de Documentación Multimedia     Open Access  
Current Science     Open Access   (Followers: 115)
Cyber-Physical Systems     Hybrid Journal  
Cyberspace : Jurnal Pendidikan Teknologi Informasi     Open Access  
DAIMI Report Series     Open Access  
Data     Open Access   (Followers: 4)
Data & Policy     Open Access   (Followers: 3)
Data Science and Engineering     Open Access   (Followers: 6)
Data Technologies and Applications     Hybrid Journal   (Followers: 208)
Data-Centric Engineering     Open Access  
Datenbank-Spektrum     Hybrid Journal   (Followers: 1)
Datenschutz und Datensicherheit - DuD     Hybrid Journal  
Decision Analytics     Open Access   (Followers: 3)
Decision Support Systems     Hybrid Journal   (Followers: 13)
Design Journal : An International Journal for All Aspects of Design     Hybrid Journal   (Followers: 33)
Digital Biomarkers     Open Access   (Followers: 1)
Digital Chemical Engineering     Open Access  
Digital Chinese Medicine     Open Access  
Digital Creativity     Hybrid Journal   (Followers: 11)
Digital Experiences in Mathematics Education     Hybrid Journal   (Followers: 2)
Digital Finance : Smart Data Analytics, Investment Innovation, and Financial Technology     Hybrid Journal   (Followers: 3)
Digital Geography and Society     Open Access  
Digital Government : Research and Practice     Open Access   (Followers: 1)
Digital Health     Open Access   (Followers: 10)
Digital Journalism     Hybrid Journal   (Followers: 7)
Digital Medicine     Open Access   (Followers: 3)
Digital Platform: Information Technologies in Sociocultural Sphere     Open Access   (Followers: 1)
Digital Policy, Regulation and Governance     Hybrid Journal   (Followers: 2)
Digital War     Hybrid Journal   (Followers: 1)
Digitale Welt : Das Wirtschaftsmagazin zur Digitalisierung     Hybrid Journal  
Digitális Bölcsészet / Digital Humanities     Open Access   (Followers: 2)
Disaster Prevention and Management     Hybrid Journal   (Followers: 30)
Discours     Open Access   (Followers: 1)
Discourse & Communication     Hybrid Journal   (Followers: 26)
Discover Internet of Things     Open Access   (Followers: 2)
Discrete and Continuous Models and Applied Computational Science     Open Access  
Discrete Event Dynamic Systems     Hybrid Journal   (Followers: 3)
Discrete Mathematics & Theoretical Computer Science     Open Access   (Followers: 1)
Discrete Optimization     Full-text available via subscription   (Followers: 7)
Displays     Hybrid Journal  
Distributed and Parallel Databases     Hybrid Journal   (Followers: 2)
e-learning and education (eleed)     Open Access   (Followers: 39)
Ecological Indicators     Hybrid Journal   (Followers: 22)
Ecological Informatics     Hybrid Journal   (Followers: 3)
Ecological Management & Restoration     Hybrid Journal   (Followers: 15)
Ecosystems     Hybrid Journal   (Followers: 32)
Edu Komputika Journal     Open Access   (Followers: 1)
Education and Information Technologies     Hybrid Journal   (Followers: 53)
Educational Philosophy and Theory     Hybrid Journal   (Followers: 10)
Educational Psychology in Practice: theory, research and practice in educational psychology     Hybrid Journal   (Followers: 13)
Educational Research and Evaluation: An International Journal on Theory and Practice     Hybrid Journal   (Followers: 7)
Educational Theory     Hybrid Journal   (Followers: 9)
Egyptian Informatics Journal     Open Access   (Followers: 5)
Electronic Commerce Research and Applications     Hybrid Journal   (Followers: 5)
Electronic Design     Partially Free   (Followers: 125)
Electronic Letters on Computer Vision and Image Analysis     Open Access   (Followers: 10)
Elektron     Open Access  
Empirical Software Engineering     Hybrid Journal   (Followers: 8)
Energy for Sustainable Development     Hybrid Journal   (Followers: 13)
Engineering & Technology     Hybrid Journal   (Followers: 22)
Engineering Applications of Computational Fluid Mechanics     Open Access   (Followers: 23)
Engineering Computations     Hybrid Journal   (Followers: 3)
Engineering Economist, The     Hybrid Journal   (Followers: 4)
Engineering Optimization     Hybrid Journal   (Followers: 19)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Enterprise Information Systems     Hybrid Journal   (Followers: 2)
Entertainment Computing     Hybrid Journal   (Followers: 2)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Environmental Communication: A Journal of Nature and Culture     Hybrid Journal   (Followers: 16)
EPJ Data Science     Open Access   (Followers: 10)
ESAIM: Control Optimisation and Calculus of Variations     Open Access   (Followers: 2)
Ethics and Information Technology     Hybrid Journal   (Followers: 64)
eTransportation     Open Access   (Followers: 1)
EURO Journal on Computational Optimization     Open Access   (Followers: 5)
EuroCALL Review     Open Access  
European Food Research and Technology     Hybrid Journal   (Followers: 8)
European Journal of Combinatorics     Full-text available via subscription   (Followers: 3)
European Journal of Computational Mechanics     Hybrid Journal   (Followers: 1)
European Journal of Information Systems     Hybrid Journal   (Followers: 85)
European Journal of Law and Technology     Open Access   (Followers: 18)
European Journal of Political Theory     Hybrid Journal   (Followers: 27)
Evolutionary Computation     Hybrid Journal   (Followers: 11)
Fibreculture Journal     Open Access   (Followers: 9)
Finite Fields and Their Applications     Full-text available via subscription   (Followers: 5)
Fixed Point Theory and Applications     Open Access  
Focus on Catalysts     Full-text available via subscription  
Focus on Pigments     Full-text available via subscription   (Followers: 3)
Focus on Powder Coatings     Full-text available via subscription   (Followers: 5)
Forensic Science International: Digital Investigation     Full-text available via subscription   (Followers: 319)
Formal Aspects of Computing     Hybrid Journal   (Followers: 3)
Formal Methods in System Design     Hybrid Journal   (Followers: 6)
Forschung     Hybrid Journal   (Followers: 1)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Databases     Full-text available via subscription   (Followers: 2)
Foundations and Trends® in Human-Computer Interaction     Full-text available via subscription   (Followers: 5)
Foundations and Trends® in Information Retrieval     Full-text available via subscription   (Followers: 30)
Foundations and Trends® in Networking     Full-text available via subscription   (Followers: 1)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 7)
Foundations and Trends® in Theoretical Computer Science     Full-text available via subscription   (Followers: 1)
Foundations of Computational Mathematics     Hybrid Journal  
Foundations of Computing and Decision Sciences     Open Access  
Frontiers in Computational Neuroscience     Open Access   (Followers: 23)
Frontiers in Computer Science     Open Access   (Followers: 1)
Frontiers in Digital Health     Open Access   (Followers: 4)
Frontiers in Digital Humanities     Open Access   (Followers: 7)
Frontiers in ICT     Open Access  
Frontiers in Neuromorphic Engineering     Open Access   (Followers: 2)
Frontiers in Research Metrics and Analytics     Open Access   (Followers: 4)
Frontiers of Computer Science in China     Hybrid Journal   (Followers: 2)
Frontiers of Environmental Science & Engineering     Hybrid Journal   (Followers: 3)
Frontiers of Information Technology & Electronic Engineering     Hybrid Journal  
Fuel Cells Bulletin     Full-text available via subscription   (Followers: 9)
Functional Analysis and Its Applications     Hybrid Journal   (Followers: 3)
Future Computing and Informatics Journal     Open Access  
Future Generation Computer Systems     Hybrid Journal   (Followers: 2)
Geo-spatial Information Science     Open Access   (Followers: 7)
Geoforum Perspektiv     Open Access  
GeoInformatica     Hybrid Journal   (Followers: 7)
Geoinformatics FCE CTU     Open Access   (Followers: 8)
GetMobile : Mobile Computing and Communications     Full-text available via subscription   (Followers: 1)
Government Information Quarterly     Hybrid Journal   (Followers: 28)
Granular Computing     Hybrid Journal  
Graphics and Visual Computing     Open Access  
Grey Room     Hybrid Journal   (Followers: 16)
Group Dynamics : Theory, Research, and Practice     Full-text available via subscription   (Followers: 15)
Groups, Complexity, Cryptology     Open Access   (Followers: 2)
HardwareX     Open Access  
Harvard Data Science Review     Open Access   (Followers: 3)
Health Services Management Research     Hybrid Journal   (Followers: 16)
Healthcare Technology Letters     Open Access  
High Frequency     Hybrid Journal  
High-Confidence Computing     Open Access   (Followers: 1)
Home Cultures     Full-text available via subscription   (Followers: 7)
Home Health Care Management & Practice     Hybrid Journal   (Followers: 1)

  First | 1 2 3 4 5 6 7 | Last

Similar Journals
Journal Cover
Foundations and Trends® in Communications and Information Theory
Journal Prestige (SJR): 2.848
Citation Impact (citeScore): 10
Number of Followers: 6  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 1567-2190 - ISSN (Online) 1567-2328
Published by Now Publishers Inc Homepage  [28 journals]
  • Rank-Metric Codes and Their Applications

    • Free pre-print version: Loading...

      Abstract: AbstractThe rank metric measures the distance between two matrices by the rank of their difference. Codes designed for the rank metric have attracted considerable attention in recent years, reinforced by network coding and further motivated by a variety of applications. In code-based cryptography, the hardness of the corresponding generic decoding problem can lead to systems with reduced public-key size. In distributed data storage, codes in the rank metric have been used repeatedly to construct codes with locality, and in coded caching, they have been employed for the placement of coded symbols. This survey gives a general introduction to rank-metric codes, explains their most important applications, and highlights their relevance to these areas of research.Suggested CitationHannes Bartz, Lukas Holzbaur, Hedongliang Liu, Sven Puchinger, Julian Renner and Antonia Wachter-Zeh (2022), "Rank-Metric Codes and Their Applications", Foundations and Trends® in Communications and Information Theory: Vol. 19: No. 3, pp 390-546. http://dx.doi.org/10.1561/0100000119
      PubDate: Mon, 02 May 2022 00:00:00 +020
       
  • Common Information, Noise Stability, and Their Extensions

    • Free pre-print version: Loading...

      Abstract: AbstractCommon information is ubiquitous in information theory and related areas such as theoretical computer science and discrete probability. However, because there are multiple notions of common information, a unified understanding of the deep interconnections between them is lacking. This monograph seeks to fill this gap by leveraging a small set of mathematical techniques that are applicable across seemingly disparate problems.In Part I, we review the operational tasks and properties associated with Wyner’s and Gács–Körner–Witsenhausen’s (GKW’s) common information. In Part II, we discuss extensions of the former from the perspective of distributed source simulation. This includes the Rényi common information which forms a bridge between Wyner’s common information and the exact common information. Via a surprising equivalence between the Rényi common information of order ∞ and the exact common information, we demonstrate the existence of a joint source in which the exact common information strictly exceeds Wyner’s common information. Other closely related topics discussed in Part II include the channel synthesis problem and the connection of Wyner’s and exact common information to the nonnegative rank of matrices.In Part III, recognizing that GKW’s common information is zero for most non-degenerate sources, we examine it with a more refined lens via the Non-Interactive Correlation Distillation (NICD) problem in which we quantify the agreement probability of extracted bits from a bivariate source. We extend this to the noise stability problem which includes as special cases the k-user NICD and q-stability problems. This allows us to seamlessly transition to discussing their connections to various conjectures in information theory and discrete probability, such as the Courtade–Kumar, Li– Médard and Mossell–O’Donnell conjectures. Finally, we consider functional inequalities (e.g., the hypercontractivity and Brascamp–Lieb inequalities), which constitute a further generalization of the noise stability problem in which the Boolean functions therein are replaced by nonnnegative functions. We demonstrate that the key ideas behind the proofs in Part III can be presented in a pedagogically coherent manner and unified via information-theoretic and Fourier-analytic methods.Suggested CitationLei Yu and Vincent Y. F. Tan (2022), "Common Information, Noise Stability, and Their Extensions", Foundations and Trends® in Communications and Information Theory: Vol. 19: No. 2, pp 107-389. http://dx.doi.org/10.1561/0100000122
      PubDate: Thu, 28 Apr 2022 00:00:00 +020
       
  • Information-Theoretic Foundations of DNA Data Storage

    • Free pre-print version: Loading...

      Abstract: AbstractDue to its longevity and enormous information density, DNA is an attractive medium for archival data storage. Natural DNA more than 700.000 years old has been recovered, and about 5 grams of DNA can in principle hold a Zetabyte of digital information, orders of magnitude more than what is achieved on conventional storage media. Thanks to rapid technological advances, DNA storage is becoming practically feasible, as demonstrated by a number of experimental storage systems, making it a promising solution for our society’s increasing need of data storage.While in living things, DNA molecules can consist of millions of nucleotides, due to technological constraints, in practice, data is stored on many short DNA molecules, which are preserved in a DNA pool and cannot be spatially ordered. Moreover, imperfections in sequencing, synthesis, and handling, as well as DNA decay during storage, introduce random noise into the system, making the task of reliably storing and retrieving information in DNA challenging.This unique setup raises a natural information-theoretic question: how much information can be reliably stored on and reconstructed from millions of short noisy sequences' The goal of this monograph is to address this question by discussing the fundamental limits of storing information on DNA. Motivated by current technological constraints on DNA synthesis and sequencing, we propose a probabilistic channel model that captures three key distinctive aspects of the DNA storage systems: (1) the data is written onto many short DNA molecules that are stored in an unordered fashion; (2) the molecules are corrupted by noise and (3) the data is read by randomly sampling from the DNA pool. Our goal is to investigate the impact of each of these key aspects on the capacity of the DNA storage system. Rather than focusing on coding-theoretic considerations and computationally efficient encoding and decoding, we aim to build an information-theoretic foundation for the analysis of these channels, developing tools for achievability and converse arguments.Suggested CitationIlan Shomorony and Reinhard Heckel (2022), "Information-Theoretic Foundations of DNA Data Storage", Foundations and Trends® in Communications and Information Theory: Vol. 19: No. 1, pp 1-106. http://dx.doi.org/10.1561/0100000117
      PubDate: Thu, 24 Feb 2022 00:00:00 +010
       
  • Asymptotic Frame Theory for Analog Coding

    • Free pre-print version: Loading...

      Abstract: AbstractOver-complete systems of vectors, or in short, frames, play the role of analog codes in many areas of communication and signal processing. To name a few, spreading sequences for code-division multiple access (CDMA), over-complete representations for multiple-description (MD) source coding, space-time codes, sensing matrices for compressed sensing (CS), and more recently, codes for unreliable distributed computation. In this survey paper we observe an informationtheoretic random-like behavior of frame subsets. Such subframes arise in setups involving erasures (communication), random user activity (multiple access), or sparsity (signal processing), in addition to channel or quantization noise. The goodness of a frame as an analog code is a function of the eigenvalues of a sub-frame, averaged over all subframes (e.g., harmonic mean of the eigenvalues relates to least-square estimation error, while geometric mean to the Shannon transform, and condition number to the restricted isometry property).Within the highly symmetric class of Equiangular Tight Frames (ETF), as well as other “near ETF” families, we show a universal behavior of the empirical eigenvalue distribution (ESD) of a randomly-selected sub-frame: (i) the ESD is asymptotically indistinguishable from Wachter’s MANOVA distribution; and (ii) it exhibits a convergence rate to this limit that is indistinguishable from that of a matrix sequence drawn from MANOVA (Jacobi) ensembles of corresponding dimensions. Some of these results follow from careful statistical analysis of empirical evidence, and some are proved analytically using random matrix theory arguments of independent interest. The goodness measures of the MANOVA limit distribution are better, in a concrete formal sense, than those of the Marchenko–Pastur distribution at the same aspect ratio, implying that deterministic analog codes are better than random (i.i.d.) analog codes. We further give evidence that the ETF (and near ETF) family is in fact superior to any other frame family in terms of its typical sub-frame goodness.Suggested CitationMarina Haikin, Matan Gavish, Dustin G. Mixon and Ram Zamir (2021), "Asymptotic Frame Theory for Analog Coding", Foundations and Trends® in Communications and Information Theory: Vol. 18: No. 4, pp 526-645. http://dx.doi.org/10.1561/0100000125
      PubDate: Thu, 18 Nov 2021 00:00:00 +010
       
  • Modeling and Optimization of Latency in Erasure-coded Storage Systems

    • Free pre-print version: Loading...

      Abstract: AbstractAs consumers are increasingly engaged in social networking and E-commerce activities, businesses grow to rely on Big Data analytics for intelligence, and traditional IT infrastructures continue to migrate to the cloud and edge, these trends cause distributed data storage demand to rise at an unprecedented speed. Erasure coding has seen itself quickly emerged as a promising technique to reduce storage cost while providing similar reliability as replicated systems, widely adopted by companies like Facebook, Microsoft and Google. However, it also brings new challenges in characterizing and optimizing the access latency when data objects are erasure coded in distributed storage. The aim of this monograph is to provide a review of recent progress (both theoretical and practical) on systems that employ erasure codes for distributed storage.In this monograph, we will first identify the key challenges and taxonomy of the research problems and then give an overview of different models and approaches that have been developed to quantify latency of erasure-coded storage. This includes recent work leveraging MDS-Reservation, Fork-Join, Probabilistic, and Delayed-Relaunch scheduling policies, as well as their applications to characterizing access latency (e.g., mean, tail, and asymptotic latency) of erasure-coded distributed storage systems. We will also extend the discussions to video streaming from erasure-coded distributed storage systems. Next, we will bridge the gap between theory and practice, and discuss lessons learned from prototype implementations. In particular, we will discuss exemplary implementations of erasure-coded storage, illuminate key design degrees of freedom and tradeoffs, and summarize remaining challenges in real-world storage systems such as in content delivery and caching. Open problems for future research are discussed at the end of each chapter.Suggested CitationVaneet Aggarwal and Tian Lan (2021), "Modeling and Optimization of Latency in Erasure-coded Storage Systems", Foundations and Trends® in Communications and Information Theory: Vol. 18: No. 3, pp 380-525. http://dx.doi.org/10.1561/0100000108
      PubDate: Wed, 07 Jul 2021 00:00:00 +020
       
  • An Algebraic and Probabilistic Framework for Network Information Theory

    • Free pre-print version: Loading...

      Abstract: AbstractIn this monograph, we develop a mathematical framework based on asymptotically good random structured codes, i.e., codes possessing algebraic properties, for network information theory. We use these codes to propose new strategies for communication in multi-terminal settings. The proposed coding strategies are applicable to arbitrary instances of the multi-terminal communication problems under consideration. In particular, we consider four fundamental problems which can be considered as building blocks of networks: distributed source coding, interference channels, multiple-access channels with distributed states and multiple description source coding. We then develop a systematic framework for characterizing the performance limits of these strategies for these problems from an information-theoretic viewpoint. Lastly, we identify several examples of the multiterminal communication problems studied herein, for which structured codes attain optimality, and provide strictly better performance as compared to classical techniques based on unstructured codes. In summary, we develop an algebraic and probabilistic framework to demonstrate the fundamental role played by structured codes in multiterminal communication problems. This monograph deals exclusively with discrete source and channel coding problems.Suggested CitationS. Sandeep Pradhan, Arun Padakandla and Farhad Shirani (2020), "An Algebraic and Probabilistic Framework for Network Information Theory", Foundations and Trends® in Communications and Information Theory: Vol. 18: No. 2, pp 173-379. http://dx.doi.org/10.1561/0100000083
      PubDate: Mon, 21 Dec 2020 00:00:00 +010
       
  • Theoretical Foundations of Adversarial Binary Detection

    • Free pre-print version: Loading...

      Abstract: AbstractThe present monograph focuses on the detection problem in adversarial setting. When framed in an adversarial setting, classical detection theory can not be applied any more, since, in order to make a correct decision, the presence of an adversary must be taken into account when designing the detector. In particular, the interplay between the Defender (), wishing to carry out the detection task, and the Attacker (), aiming at impeding it, must be investigated. The purpose of this monograph is to lay out the foundations of a general theory of adversarial detection, taking into account the impact that the presence of the adversary has on the design of the optimal detector. We do so by casting the adversarial detection problem into a game theoretical framework, which is then studied by relying on typical methods of information theory. As a final result, the theory allows to state the conditions under which both the false positive and false negative error probabilities tend to zero exponentially fast, and to relate the error exponents of the two kinds of errors to the distortion the attacker can introduce into the test sequence.Suggested CitationMauro Barni and Benedetta Tondi (2020), "Theoretical Foundations of Adversarial Binary Detection", Foundations and Trends® in Communications and Information Theory: Vol. 18: No. 1, pp 1-172. http://dx.doi.org/10.1561/0100000102
      PubDate: Sun, 20 Dec 2020 00:00:00 +010
       
  • Polynomial Methods in Statistical Inference: Theory and Practice

    • Free pre-print version: Loading...

      Abstract: AbstractThis survey provides an exposition of a suite of techniques based on the theory of polynomials, collectively referred to as polynomial methods, which have recently been applied to address several challenging problems in statistical inference successfully. Topics including polynomial approximation, polynomial interpolation and majorization, moment space and positive polynomials, orthogonal polynomials and Gaussian quadrature are discussed, with their major probabilistic and statistical applications in property estimation on large domains and learning mixture models. These techniques provide useful tools not only for the design of highly practical algorithms with provable optimality, but also for establishing the fundamental limits of the inference problems through the method of moment matching. The effectiveness of the polynomial method is demonstrated in concrete problems such as entropy and support size estimation, distinct elements problem, and learning Gaussian mixture models.Suggested CitationYihong Wu and Pengkun Yang (2020), "Polynomial Methods in Statistical Inference: Theory and Practice", Foundations and Trends® in Communications and Information Theory: Vol. 17: No. 4, pp 402-586. http://dx.doi.org/10.1561/0100000095
      PubDate: Mon, 12 Oct 2020 00:00:00 +020
       
  • Information-Theoretic Foundations of Mismatched Decoding

    • Free pre-print version: Loading...

      Abstract: AbstractShannon’s channel coding theorem characterizes the maximalrate of information that can be reliably transmittedover a communication channel when optimal encoding anddecoding strategies are used. In many scenarios, however,practical considerations such as channel uncertainty andimplementation constraints rule out the use of an optimaldecoder. The mismatched decoding problem addresses suchscenarios by considering the case that the decoder cannotbe optimized, but is instead fixed as part of the problemstatement. This problem is not only of direct interest inits own right, but also has close connections with otherlong-standing theoretical problems in information theory.In this monograph, we survey both classical literature andrecent developments on the mismatched decoding problem,with an emphasis on achievable random-coding rates formemoryless channels. We present two widely-consideredachievable rates known as the generalized mutual information(GMI) and the LM rate, and overview their derivationsand properties. In addition, we survey several improved ratesvia multi-user coding techniques, as well as recent developmentsand challenges in establishing upper bounds on themismatch capacity, and an analogous mismatched encodingproblem in rate-distortion theory. Throughout the monograph,we highlight a variety of applications and connectionswith other prominent information theory problems.Suggested CitationJonathan Scarlett, Albert Guillén i Fàbregas, Anelia Somekh-Baruch and Alfonso Martinez (2020), "Information-Theoretic Foundations of Mismatched Decoding", Foundations and Trends® in Communications and Information Theory: Vol. 17: No. 2. http://dx.doi.org/10.1561/0100000101
      PubDate: Wed, 30 Sep 2020 00:00:00 +020
       
  • Coded Computing

    • Free pre-print version: Loading...

      Abstract: AbstractWe introduce the concept of “coded computing”, a novelcomputing paradigm that utilizes coding theory to effectivelyinject and leverage data/computation redundancyto mitigate several fundamental bottlenecks in large-scaledistributed computing, namely communication bandwidth,straggler’s (i.e., slow or failing nodes) delay, privacy andsecurity bottlenecks. More specifically, for MapReduce baseddistributed computing structures, we propose the “CodedDistributed Computing” (CDC) scheme, which injects redundantcomputations across the network in a structuredmanner, such that in-network coding opportunities are enabledto substantially slash the communication load to shufflethe intermediate computation results. We prove thatCDC achieves the optimal tradeoff between computationand communication, and demonstrate its impact on a widerange of distributed computing systems from cloud-baseddatacenters to mobile edge/fog computing platforms.Secondly, to alleviate the straggler effect that prolongs theexecutions of distributed machine learning algorithms, weutilize the ideas from error correcting codes to develop“Polynomial Codes” for computing general matrix algebra,and “Lagrange Coded Computing” (LCC) for computingarbitrary multivariate polynomials. The core idea of theseproposed schemes is to apply coding to create redundantdata/computation scattered across the network, such thatcompleting the overall computation task only requires a subsetof the network nodes returning their local computationresults. We demonstrate the optimality of Polynomial Codesand LCC in minimizing the computation latency, by provingthat they require the least number of nodes to return theirresults.Finally, we illustrate the role of coded computing in providingsecurity and privacy in distributed computing andmachine learning. In particular, we consider the problems ofsecure multiparty computing (MPC) and privacy-preservingmachine learning, and demonstrate how coded computingcan be leveraged to provide efficient solutions to these criticalproblems and enable substantial improvements over thestate of the art.To illustrate the impact of coded computing on real worldapplications and systems, we implement the proposed codingschemes on cloud-based distributed computing systems, andsignificantly improve the run-time performance of importantbenchmarks including distributed sorting, distributed trainingof regression models, and privacy-preserving training forimage classification. Throughout this monograph, we alsohighlight numerous open problems and exciting researchdirections for future work on coded computing.Suggested CitationSongze Li and Salman Avestimehr (2020), "Coded Computing", Foundations and Trends® in Communications and Information Theory: Vol. 17: No. 1, pp 1-148. http://dx.doi.org/10.1561/0100000103
      PubDate: Thu, 30 Jul 2020 00:00:00 +020
       
  • Cache Optimization Models and Algorithms

    • Free pre-print version: Loading...

      Abstract: AbstractCaching refers to the act of replicating information at afaster (or closer) medium with the purpose of improvingperformance. This deceptively simple idea has given rise tosome of the hardest optimization problems in the fields ofcomputer systems, networking, and the Internet, many ofwhich remain unsolved several years after their conception.While a wealth of research contributions exists from the topicsof memory systems, data centers, Internet traffic, CDNs,and recently wireless networks, the literature is dispersedand overlapping at times. In this monograph, we take a Q1unifying modeling view: by focusing on the fundamental underlyingmathematical models, we re-organize the availablematerial into a powerful framework for performing optimizationof caching systems. This way, we aspire to present asolid background for the anticipated explosion in cachingresearch, but also provide a didactic view into how engineershave managed to infuse mathematical models into the studyof caching over the last 40 years.Suggested CitationGeorgios Paschos, George Iosifidis and Giuseppe Caire (2020), "Cache Optimization Models and Algorithms", Foundations and Trends® in Communications and Information Theory: Vol. 16: No. 3-4, pp 156-343. http://dx.doi.org/10.1561/0100000104
      PubDate: Thu, 30 Jul 2020 00:00:00 +020
       
  • Lattice-Reduction-Aided and Integer-Forcing Equalization: Structures,
           Criteria, Factorization, and Coding

    • Free pre-print version: Loading...

      Abstract: AbstractIn this monograph, a tutorial review of lattice-reductionaided(LRA) and integer-forcing (IF) equalization approachesinMIMO communications is given. Both methods have incommon that integer linear combinations are decoded; theremaining integer interference is resolved subsequently. Theaim is to enlighten similarities and differences of both approaches.The various criteria for selecting the integer linearcombinations available in the literature are summarized in aunified way. Thereby, we clearly distinguish between the criteriaaccording to which the non-integer equalization partis optimized and those, which are inherently considered inthe applied lattice algorithms, i.e., constraints on the integerequalization part. The demands on the signal constellationsand coding schemes are discussed in detail. We treatLRA/IF approaches for receiver-side linear equalization anddecision-feedback equalization, as well as transmitter-sidelinear preequalization and precoding.Suggested CitationRobert F. H. Fischer, Sebastian Stern and Johannes B. Huber (2019), "Lattice-Reduction-Aided andInteger-Forcing Equalization: Structures, Criteria, Factorization, and Coding", Foundations and Trends® in Communications and Information Theory: Vol. 16: No. 1-2, pp 1-155. http://dx.doi.org/10.1561/0100000100
      PubDate: Mon, 09 Dec 2019 00:00:00 +010
       
  • Group Testing: An Information Theory Perspective

    • Free pre-print version: Loading...

      Abstract: AbstractThe group testing problem concerns discovering a smallnumber of defective items within a large population byperforming tests on pools of items. A test is positive ifthe pool contains at least one defective, and negative if itcontains no defectives. This is a sparse inference problemwith a combinatorial flavour, with applications in medicaltesting, biology, telecommunications, information technology,data science, and more.In this monograph, we survey recent developments in thegroup testing problem from an information-theoretic perspective.We cover several related developments: efficientalgorithms with practical storage and computation requirements,achievability bounds for optimal decoding methods,and algorithm-independent converse bounds. We assess thetheoretical guarantees not only in terms of scaling laws,but also in terms of the constant factors, leading to thenotion of the rate of group testing, indicating the amountof information learned per test. Considering both noiselessand noisy settings, we identify several regimes where existingalgorithms are provably optimal or near-optimal, aswell as regimes where there remains greater potential forimprovement.In addition, we survey results concerning a number of variationson the standard group testing problem, includingpartial recovery criteria, adaptive algorithms with a limitednumber of stages, constrained test designs, and sublineartimealgorithms.Suggested CitationMatthew Aldridge, Oliver Johnson and Jonathan Scarlett (2019), "Group Testing: An Information Theory Perspective", Foundations and Trends® in Communications and Information Theory: Vol. 15: No. 3-4, pp 196-392. http://dx.doi.org/10.1561/0100000099
      PubDate: Thu, 05 Dec 2019 00:00:00 +010
       
  • Sparse Regression Codes

    • Free pre-print version: Loading...

      Abstract: AbstractDeveloping computationally-efficient codes that approach the Shannon-theoretic limits for communication and compression has long been one of the major goals of information and coding theory. There have been significant advances towards this goal in the last couple of decades, with the emergence of turbo codes, sparsegraph codes, and polar codes. These codes are designed primarily for discrete-alphabet channels and sources. For Gaussian channels and sources, where the alphabet is inherently continuous, Sparse Superposition Codes or Sparse Regression Codes (SPARCs) are a promising class of codes for achieving the Shannon limits. This monograph provides a unified and comprehensive over-view of sparse regression codes, covering theory, algorithms, and practical implementation aspects. The first part of the monograph focuses on SPARCs for AWGN channel coding, and the second part on SPARCs for lossy compression (with squared error distortion criterion). In the third part, SPARCs are used to construct codes for Gaussian multi-terminal channel and source coding models such as broadcast channels, multiple-access channels, and source and channel coding with side information. The monograph concludes with a discussion of open problems and directions for future work.Suggested CitationRamji Venkataramanan, Sekhar Tatikonda and Andrew Barron (2019), "Sparse Regression Codes", Foundations and Trends® in Communications and Information Theory: Vol. 15: No. 1-2, pp 1-195. http://dx.doi.org/10.1561/0100000092
      PubDate: Thu, 20 Jun 2019 00:00:00 +020
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 100.24.115.215
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-