Pub Date : 2024-11-11DOI: 10.1109/JSAIT.2024.3496197
Yasutada Oohama
We consider the one helper source coding problem posed and investigated by Ahlswede, Körner, and Wyner for a class of information sources with memory. For this class of information sources we give explicit inner and outer bounds of the admissible rate region. We also give a certain nontrivial class of information sources where the inner and outer bounds match.
{"title":"Source Coding for Markov Sources With Partial Memoryless Side Information at the Decoder","authors":"Yasutada Oohama","doi":"10.1109/JSAIT.2024.3496197","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3496197","url":null,"abstract":"We consider the one helper source coding problem posed and investigated by Ahlswede, Körner, and Wyner for a class of information sources with memory. For this class of information sources we give explicit inner and outer bounds of the admissible rate region. We also give a certain nontrivial class of information sources where the inner and outer bounds match.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"675-693"},"PeriodicalIF":0.0,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10750312","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-31DOI: 10.1109/JSAIT.2024.3487856
Yichen Huang
In a spin chain governed by a local Hamiltonian, we consider a microcanonical ensemble in the middle of the energy spectrum and a contiguous subsystem whose length is a constant fraction of the system size. We prove that if the bandwidth of the ensemble is greater than a certain constant, then the average entanglement entropy (between the subsystem and the rest of the system) of eigenstates in the ensemble deviates from the maximum entropy by at least a positive constant. This result highlights the difference between the entanglement entropy of mid-spectrum eigenstates of (chaotic) local Hamiltonians and that of random states. We also prove that the former deviates from the thermodynamic entropy at the same energy by at least a positive constant.
{"title":"Deviation From Maximal Entanglement for Mid-Spectrum Eigenstates of Local Hamiltonians","authors":"Yichen Huang","doi":"10.1109/JSAIT.2024.3487856","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3487856","url":null,"abstract":"In a spin chain governed by a local Hamiltonian, we consider a microcanonical ensemble in the middle of the energy spectrum and a contiguous subsystem whose length is a constant fraction of the system size. We prove that if the bandwidth of the ensemble is greater than a certain constant, then the average entanglement entropy (between the subsystem and the rest of the system) of eigenstates in the ensemble deviates from the maximum entropy by at least a positive constant. This result highlights the difference between the entanglement entropy of mid-spectrum eigenstates of (chaotic) local Hamiltonians and that of random states. We also prove that the former deviates from the thermodynamic entropy at the same energy by at least a positive constant.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"694-701"},"PeriodicalIF":0.0,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825942","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}
Pub Date : 2024-10-14DOI: 10.1109/JSAIT.2024.3481296
Tomer Berg;Or Ordentlich;Ofer Shayevitz
The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a function of the number of available samples, with far less attention given to the effect of memory limitations on performance. Recently, this latter topic has drawn much interest in the engineering and computer science literature. In this survey paper, we attempt to review the state-of-the-art of statistical inference under memory constraints in several canonical problems, including hypothesis testing, parameter estimation, and distribution property testing/estimation. We discuss the main results in this developing field, and by identifying recurrent themes, we extract some fundamental building blocks for algorithmic construction, as well as useful techniques for lower bound derivations.
{"title":"Statistical Inference With Limited Memory: A Survey","authors":"Tomer Berg;Or Ordentlich;Ofer Shayevitz","doi":"10.1109/JSAIT.2024.3481296","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3481296","url":null,"abstract":"The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a function of the number of available samples, with far less attention given to the effect of memory limitations on performance. Recently, this latter topic has drawn much interest in the engineering and computer science literature. In this survey paper, we attempt to review the state-of-the-art of statistical inference under memory constraints in several canonical problems, including hypothesis testing, parameter estimation, and distribution property testing/estimation. We discuss the main results in this developing field, and by identifying recurrent themes, we extract some fundamental building blocks for algorithmic construction, as well as useful techniques for lower bound derivations.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"623-644"},"PeriodicalIF":0.0,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595119","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}
Pub Date : 2024-09-30DOI: 10.1109/JSAIT.2024.3469929
Michael G. Jabbour;Nilanjana Datta
Uniform continuity bounds on entropies are generally expressed in terms of a single distance measure between probability distributions or quantum states, typically, the total variation- or trace distance. However, if an additional distance measure is known, the continuity bounds can be significantly strengthened. Here, we prove a tight uniform continuity bound for the Shannon entropy in terms of both the local- and total variation distances, sharpening an inequality in (Sason, 2013). We also obtain a uniform continuity bound for the von Neumann entropy in terms of both the operator norm- and trace distances. We then apply our results to compute upper bounds on channel capacities. We first refine the concept of approximate degradable channels by introducing $(varepsilon ,nu)$ –degradable channels. These are $varepsilon $ –close in diamond norm and $nu $ –close in completely bounded spectral norm to their complementary channel when composed with a degrading channel. This leads to improved upper bounds to the quantum- and private classical capacities of such channels. Moreover, these bounds can be further improved by considering certain unstabilized versions of the above norms. We show that upper bounds on the latter can be efficiently expressed as semidefinite programs. As an application, we obtain a new upper bound on the quantum capacity of the qubit depolarizing channel.
{"title":"Tightening Continuity Bounds for Entropies and Bounds on Quantum Capacities","authors":"Michael G. Jabbour;Nilanjana Datta","doi":"10.1109/JSAIT.2024.3469929","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3469929","url":null,"abstract":"Uniform continuity bounds on entropies are generally expressed in terms of a single distance measure between probability distributions or quantum states, typically, the total variation- or trace distance. However, if an additional distance measure is known, the continuity bounds can be significantly strengthened. Here, we prove a tight uniform continuity bound for the Shannon entropy in terms of both the local- and total variation distances, sharpening an inequality in (Sason, 2013). We also obtain a uniform continuity bound for the von Neumann entropy in terms of both the operator norm- and trace distances. We then apply our results to compute upper bounds on channel capacities. We first refine the concept of approximate degradable channels by introducing \u0000<inline-formula> <tex-math>$(varepsilon ,nu)$ </tex-math></inline-formula>\u0000–degradable channels. These are \u0000<inline-formula> <tex-math>$varepsilon $ </tex-math></inline-formula>\u0000–close in diamond norm and \u0000<inline-formula> <tex-math>$nu $ </tex-math></inline-formula>\u0000–close in completely bounded spectral norm to their complementary channel when composed with a degrading channel. This leads to improved upper bounds to the quantum- and private classical capacities of such channels. Moreover, these bounds can be further improved by considering certain unstabilized versions of the above norms. We show that upper bounds on the latter can be efficiently expressed as semidefinite programs. As an application, we obtain a new upper bound on the quantum capacity of the qubit depolarizing channel.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"645-658"},"PeriodicalIF":0.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645509","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}
Pub Date : 2024-09-23DOI: 10.1109/JSAIT.2024.3466649
Sundara Rajan Srinivasavaradhan;Pavlos Nikolopoulos;Christina Fragouli;Suhas Diggavi
Proactive testing and interventions are crucial for disease containment during a pandemic until widespread vaccination is achieved. However, a key challenge remains: Can we accurately identify all new daily infections with only a fraction of tests needed compared to testing everyone, everyday? Group testing reduces the number of tests but overlooks infection dynamics and non i.i.d nature of infections in a community, while on the other hand traditional SIR (Susceptible-Infected-Recovered) models address these dynamics but don’t integrate discrete-time testing and interventions. This paper bridges the gap. We propose a “discrete-time SIR stochastic block model” that incorporates group testing and daily interventions, as a discrete counterpart to the well-known continuous-time SIR model that reflects community structure through a specific weighted graph. We analyze the model to determine the minimum number of daily group tests required to identify all infections with vanishing error probability. We find that one can leverage the knowledge of the community and the model to inform nonadaptive group testing algorithms that are order-optimal, and therefore achieve the same performance as complete testing using a much smaller number of tests.
在实现大范围疫苗接种之前，主动检测和干预对于大流行期间的疾病控制至关重要。然而，关键的挑战依然存在：与每天对每个人进行检测相比，我们能否只用一小部分检测就能准确识别每天所有的新感染病例？集体检测减少了检测次数，但却忽略了社区中的感染动态和感染的非即期性，而另一方面，传统的 SIR（易感者-感染者-康复者）模型解决了这些动态问题，但却没有整合离散时间检测和干预措施。本文弥补了这一不足。我们提出了一种 "离散时间 SIR 随机区块模型"，该模型结合了分组检测和日常干预，是著名的连续时间 SIR 模型的离散对应模型，后者通过特定的加权图反映社区结构。我们对该模型进行了分析，以确定以消失的误差概率识别所有感染所需的最小每日分组测试次数。我们发现，我们可以利用对群体和模型的了解，为非适应性群体测试算法提供信息，这种算法是阶次最优的，因此可以用更少的测试次数达到与完全测试相同的性能。
{"title":"Dynamic Group Testing to Control and Monitor Disease Progression in a Population","authors":"Sundara Rajan Srinivasavaradhan;Pavlos Nikolopoulos;Christina Fragouli;Suhas Diggavi","doi":"10.1109/JSAIT.2024.3466649","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3466649","url":null,"abstract":"Proactive testing and interventions are crucial for disease containment during a pandemic until widespread vaccination is achieved. However, a key challenge remains: Can we accurately identify all new daily infections with only a fraction of tests needed compared to testing everyone, everyday? Group testing reduces the number of tests but overlooks infection dynamics and non i.i.d nature of infections in a community, while on the other hand traditional SIR (Susceptible-Infected-Recovered) models address these dynamics but don’t integrate discrete-time testing and interventions. This paper bridges the gap. We propose a “discrete-time SIR stochastic block model” that incorporates group testing and daily interventions, as a discrete counterpart to the well-known continuous-time SIR model that reflects community structure through a specific weighted graph. We analyze the model to determine the minimum number of daily group tests required to identify all infections with vanishing error probability. We find that one can leverage the knowledge of the community and the model to inform nonadaptive group testing algorithms that are order-optimal, and therefore achieve the same performance as complete testing using a much smaller number of tests.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"609-622"},"PeriodicalIF":0.0,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524175","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}
Pub Date : 2024-09-20DOI: 10.1109/JSAIT.2024.3465022
Michael Gastpar;Erixhen Sula
The Shannon lower bound has been the subject of several important contributions by Berger. This paper surveys Shannon bounds on rate-distortion problems under mean-squared error distortion with a particular emphasis on Berger’s techniques. Moreover, as a new result, the Gray-Wyner network is added to the canon of settings for which such bounds are known. In the Shannon bounding technique, elegant lower bounds are expressed in terms of the source entropy power. Moreover, there is often a complementary upper bound that involves the source variance in such a way that the bounds coincide in the special case of Gaussian statistics. Such pairs of bounds are sometimes referred to as Shannon bounds. The present paper puts Berger’s work on many aspects of this problem in the context of more recent developments, encompassing indirect and remote source coding such as the CEO problem, originally proposed by Berger, as well as the Gray-Wyner network as a new contribution.
香农下界是伯杰数次重要贡献的主题。本文研究了均方误差失真条件下速率失真问题的香农下界，并特别强调了伯杰的技术。此外，作为一项新成果，格雷-维纳网络也被添加到已知此类约束的环境中。在香农约束技术中，优雅的下限用源熵功率表示。此外，在高斯统计的特殊情况下，通常会有一个涉及源方差的互补上界，使两者的边界重合。这样的边界对有时被称为香农边界。本文将伯杰在这一问题的许多方面所做的工作与最近的发展结合起来，包括间接和远程源编码，如伯杰最初提出的 CEO 问题，以及作为新贡献的格雷-惠纳网络。
{"title":"Shannon Bounds for Quadratic Rate-Distortion Problems","authors":"Michael Gastpar;Erixhen Sula","doi":"10.1109/JSAIT.2024.3465022","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3465022","url":null,"abstract":"The Shannon lower bound has been the subject of several important contributions by Berger. This paper surveys Shannon bounds on rate-distortion problems under mean-squared error distortion with a particular emphasis on Berger’s techniques. Moreover, as a new result, the Gray-Wyner network is added to the canon of settings for which such bounds are known. In the Shannon bounding technique, elegant lower bounds are expressed in terms of the source entropy power. Moreover, there is often a complementary upper bound that involves the source variance in such a way that the bounds coincide in the special case of Gaussian statistics. Such pairs of bounds are sometimes referred to as Shannon bounds. The present paper puts Berger’s work on many aspects of this problem in the context of more recent developments, encompassing indirect and remote source coding such as the CEO problem, originally proposed by Berger, as well as the Gray-Wyner network as a new contribution.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"597-608"},"PeriodicalIF":0.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452676","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}
Pub Date : 2024-09-02DOI: 10.1109/JSAIT.2024.3453273
Ruze Zhang;Xuan Guang;Shenghao Yang;Xueyan Niu;Bo Bai
In this paper, the problem of zero-error network function computation is considered, where in a directed acyclic network, a single sink node is required to compute with zero error a function of the source messages that are separately generated by multiple source nodes. From the information-theoretic point of view, we are interested in the fundamental computing capacity, which is defined as the average number of times that the function can be computed with zero error for one use of the network. The explicit characterization of the computing capacity in general is overwhelming difficult. The best known upper bound applicable to arbitrary network topologies and arbitrary target functions is the one proved by Guang et al. in using an approach of the cut-set strong partition. This bound is tight for all previously considered network function computation problems whose computing capacities are known. In this paper, we consider the model of computing the binary arithmetic sum over an asymmetric diamond network, which is of great importance to illustrate the combinatorial nature of network function computation problem. First, we prove a corrected upper bound 1 by using a linear programming approach, which corrects an invalid bound previously claimed in the literature. Nevertheless, this upper bound cannot bring any improvement over the best known upper bound for this model, which is also equal to 1. Further, by developing a different graph coloring approach, we obtain an improved upper bound ${}frac {1}{log _{3} 2+log 3-1}~(approx 0.822)$ . We thus show that the best known upper bound proved by Guang et al. is not tight for this model which answers the open problem that whether this bound in general is tight. On the other hand, we present an explicit code construction, which implies a lower bound ${}frac {1}{2}log _{3}6~(approx 0.815)$ on the computing capacity. Comparing the improved upper and lower bounds thus obtained, there exists a rough 0.007 gap between them.
{"title":"Computation of Binary Arithmetic Sum Over an Asymmetric Diamond Network","authors":"Ruze Zhang;Xuan Guang;Shenghao Yang;Xueyan Niu;Bo Bai","doi":"10.1109/JSAIT.2024.3453273","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3453273","url":null,"abstract":"In this paper, the problem of zero-error network function computation is considered, where in a directed acyclic network, a single sink node is required to compute with zero error a function of the source messages that are separately generated by multiple source nodes. From the information-theoretic point of view, we are interested in the fundamental computing capacity, which is defined as the average number of times that the function can be computed with zero error for one use of the network. The explicit characterization of the computing capacity in general is overwhelming difficult. The best known upper bound applicable to arbitrary network topologies and arbitrary target functions is the one proved by Guang et al. in using an approach of the cut-set strong partition. This bound is tight for all previously considered network function computation problems whose computing capacities are known. In this paper, we consider the model of computing the binary arithmetic sum over an asymmetric diamond network, which is of great importance to illustrate the combinatorial nature of network function computation problem. First, we prove a corrected upper bound 1 by using a linear programming approach, which corrects an invalid bound previously claimed in the literature. Nevertheless, this upper bound cannot bring any improvement over the best known upper bound for this model, which is also equal to 1. Further, by developing a different graph coloring approach, we obtain an improved upper bound \u0000<inline-formula> <tex-math>${}frac {1}{log _{3} 2+log 3-1}~(approx 0.822)$ </tex-math></inline-formula>\u0000. We thus show that the best known upper bound proved by Guang et al. is not tight for this model which answers the open problem that whether this bound in general is tight. On the other hand, we present an explicit code construction, which implies a lower bound \u0000<inline-formula> <tex-math>${}frac {1}{2}log _{3}6~(approx 0.815)$ </tex-math></inline-formula>\u0000 on the computing capacity. Comparing the improved upper and lower bounds thus obtained, there exists a rough 0.007 gap between them.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"585-596"},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320442","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}
Pub Date : 2024-08-28DOI: 10.1109/JSAIT.2024.3451240
Nadim Ghaddar;Lele Wang
The problem of coding for the uplink and downlink of cloud radio access networks (C-RAN’s) with K users and L relays is considered. It is shown that low-complexity coding schemes that achieve any point in the rate-fronthaul region of joint coding and compression can be constructed starting from at most $4(K+L)-2$ point-to-point codes designed for symmetric channels. This reduces the seemingly hard task of constructing good codes for C-RAN’s to the much better understood task of finding good codes for single-user channels. To show this result, an equivalence between the achievable rate-fronthaul regions of joint coding and successive coding is established. Then, rate-splitting and quantization-splitting techniques are used to show that the task of achieving a rate-fronthaul point in the joint coding region can be simplified to that of achieving a corner point in a higher-dimensional C-RAN problem. As a by-product, some interesting properties of the rate-fronthaul region of joint decoding for uplink C-RAN’s are also derived.
本文研究了具有 K 个用户和 L 个中继站的云无线接入网（C-RAN）的上下行链路编码问题。研究表明，可以从最多 $4(K+L)-2$ 为对称信道设计的点对点编码开始，构建低复杂度编码方案，以实现联合编码和压缩的速率-链路区域内的任意点。这就把为 C-RAN 构建良好编码这一看似艰巨的任务简化为为单用户信道寻找良好编码这一更好理解的任务。为了证明这一结果，我们建立了联合编码和连续编码的可实现速率-频带区域之间的等价关系。然后，利用速率拆分和量化拆分技术来说明，在联合编码区域实现速率-频带点的任务可以简化为在高维 C-RAN 问题中实现角点的任务。作为副产品，还得出了上行链路 C-RAN 联合解码区域的一些有趣特性。
{"title":"Low-Complexity Coding Techniques for Cloud Radio Access Networks","authors":"Nadim Ghaddar;Lele Wang","doi":"10.1109/JSAIT.2024.3451240","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3451240","url":null,"abstract":"The problem of coding for the uplink and downlink of cloud radio access networks (C-RAN’s) with K users and L relays is considered. It is shown that low-complexity coding schemes that achieve any point in the rate-fronthaul region of joint coding and compression can be constructed starting from at most \u0000<inline-formula> <tex-math>$4(K+L)-2$ </tex-math></inline-formula>\u0000 point-to-point codes designed for symmetric channels. This reduces the seemingly hard task of constructing good codes for C-RAN’s to the much better understood task of finding good codes for single-user channels. To show this result, an equivalence between the achievable rate-fronthaul regions of joint coding and successive coding is established. Then, rate-splitting and quantization-splitting techniques are used to show that the task of achieving a rate-fronthaul point in the joint coding region can be simplified to that of achieving a corner point in a higher-dimensional C-RAN problem. As a by-product, some interesting properties of the rate-fronthaul region of joint decoding for uplink C-RAN’s are also derived.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"572-584"},"PeriodicalIF":0.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275002","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}
This article addresses errors in [1] . Equation (2) contained an error wherein x was not bold. It is corrected below.
本文解决了 [1] 中的错误。公式(2)中有一处错误，其中 x 没有加粗。现更正如下。
{"title":"Erratum to “LightVeriFL: A Lightweight and Verifiable Secure Aggregation for Federated Learning”","authors":"Baturalp Buyukates;Jinhyun So;Hessam Mahdavifar;Salman Avestimehr","doi":"10.1109/JSAIT.2024.3413928","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3413928","url":null,"abstract":"This article addresses errors in \u0000<xref>[1]</xref>\u0000. \u0000<xref>Equation (2)</xref>\u0000 contained an error wherein x was not bold. It is corrected below.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"570-571"},"PeriodicalIF":0.0,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142077637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.1109/JSAIT.2024.3422011
Ahmed H. Salamah;Kaixiang Zheng;Linfeng Ye;En-Hui Yang
Conventional image compression techniques are primarily developed for the human visual system. However, with the extensive use of deep neural networks (DNNs) for computer vision, more and more images will be consumed by DNN-based intelligent machines, which makes it crucial to develop image compression techniques customized for DNN vision while being JPEG compliant. In this paper, we revisit the JPEG rate distortion theory for DNN vision. First, we propose a novel distortion measure, dubbed the sensitivity weighted error (SWE), for DNN vision. Second, we incorporate SWE into the soft decision quantization (SDQ) process of JPEG to trade SWE for rate. Finally, we develop an algorithm, called OptS, for designing optimal quantization tables for the luminance channel and chrominance channels, respectively. To test the performance of the resulting DNN-oriented compression framework and algorithm, experiments of image classification are conducted on the ImageNet dataset for four prevalent DNN models. Results demonstrate that our proposed framework and algorithm achieve better rate-accuracy (R-A) performance than the default JPEG. For some DNN models, our proposed framework and algorithm provide a significant reduction in the compression rate up to 67.84% with no accuracy loss compared to the default JPEG.
{"title":"JPEG Compliant Compression for DNN Vision","authors":"Ahmed H. Salamah;Kaixiang Zheng;Linfeng Ye;En-Hui Yang","doi":"10.1109/JSAIT.2024.3422011","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3422011","url":null,"abstract":"Conventional image compression techniques are primarily developed for the human visual system. However, with the extensive use of deep neural networks (DNNs) for computer vision, more and more images will be consumed by DNN-based intelligent machines, which makes it crucial to develop image compression techniques customized for DNN vision while being JPEG compliant. In this paper, we revisit the JPEG rate distortion theory for DNN vision. First, we propose a novel distortion measure, dubbed the sensitivity weighted error (SWE), for DNN vision. Second, we incorporate SWE into the soft decision quantization (SDQ) process of JPEG to trade SWE for rate. Finally, we develop an algorithm, called OptS, for designing optimal quantization tables for the luminance channel and chrominance channels, respectively. To test the performance of the resulting DNN-oriented compression framework and algorithm, experiments of image classification are conducted on the ImageNet dataset for four prevalent DNN models. Results demonstrate that our proposed framework and algorithm achieve better rate-accuracy (R-A) performance than the default JPEG. For some DNN models, our proposed framework and algorithm provide a significant reduction in the compression rate up to 67.84% with no accuracy loss compared to the default JPEG.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"5 ","pages":"520-533"},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966001","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}
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