IEEE journal on selected areas in information theory最新文献

2024 Index IEEE Journal on Selected Areas in Information Theory Vol. 5 《信息理论的选择领域》第5卷

IEEE journal on selected areas in information theory Pub Date : 2025-01-13 DOI: 10.1109/JSAIT.2025.3528825

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JSAIT Issue on Information-Theoretic Methods for Trustworthy and Reliable Machine Learning JSAIT关于可信和可靠机器学习的信息论方法

IEEE journal on selected areas in information theory Pub Date : 2025-01-07 DOI: 10.1109/JSAIT.2024.3508492

Lalitha Sankar;Oliver Kosut;Flavio Calmon;Ayfer Ozgur;Lele Wang;Ofer Shayevitz;Parastoo Sadeghi

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Editorial Data, Physics, and Life Through the Lens of Information Theory 信息理论视角下的编辑数据、物理和生命

IEEE journal on selected areas in information theory Pub Date : 2025-01-06 DOI: 10.1109/JSAIT.2024.3499012

Jun Chen;Jerry Gibson;Ioannis Kontoyiannis;Yingbin Liang;S. Sandeep Pradhan;Andreas Winter;Ram Zamir;Richard E. Blahut;Yasutada Oohama;Aaron B. Wagner;Raymond W. Yeung

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Board of Governors 理事会

IEEE journal on selected areas in information theory Pub Date : 2025-01-06 DOI: 10.1109/JSAIT.2024.3519913

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Rate-Distortion-Perception Tradeoff for Gaussian Vector Sources

IEEE journal on selected areas in information theory Pub Date : 2024-11-29 DOI: 10.1109/JSAIT.2024.3509420

Jingjing Qian;Sadaf Salehkalaibar;Jun Chen;Ashish Khisti;Wei Yu;Wuxian Shi;Yiqun Ge;Wen Tong

{"title":"Rate-Distortion-Perception Tradeoff for Gaussian Vector Sources","authors":"Jingjing Qian;Sadaf Salehkalaibar;Jun Chen;Ashish Khisti;Wei Yu;Wuxian Shi;Yiqun Ge;Wen Tong","doi":"10.1109/JSAIT.2024.3509420","DOIUrl":"https://doi.org/10.1109/JSAIT.2024.3509420","url":null,"abstract":"This paper studies the rate-distortion-perception (RDP) tradeoff for a Gaussian vector source coding problem where the goal is to compress the multi-component source subject to distortion and perception constraints. Specifically, the RDP setting with either the Kullback-Leibler (KL) divergence or Wasserstein-2 metric as the perception loss function is examined, and it is shown that for Gaussian vector sources, jointly Gaussian reconstructions are optimal. We further demonstrate that the optimal tradeoff can be expressed as an optimization problem, which can be explicitly solved. An interesting property of the optimal solution is as follows. Without the perception constraint, the traditional reverse water-filling solution for characterizing the rate-distortion (RD) tradeoff of a Gaussian vector source states that the optimal rate allocated to each component depends on a constant, called the water level. If the variance of a specific component is below the water level, it is assigned a zero compression rate. However, with active distortion and perception constraints, we show that the optimal rates allocated to the different components are always positive. Moreover, the water levels that determine the optimal rate allocation for different components are unequal. We further treat the special case of perceptually perfect reconstruction and study its RDP function in the high-distortion and low-distortion regimes to obtain insight to the structure of the optimal solution.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"6 ","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143107142","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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Source Coding for Markov Sources With Partial Memoryless Side Information at the Decoder 解码器中具有部分无记忆侧信息的马尔可夫源编码

IEEE journal on selected areas in information theory Pub Date : 2024-11-11 DOI: 10.1109/JSAIT.2024.3496197

Yasutada Oohama

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Deviation From Maximal Entanglement for Mid-Spectrum Eigenstates of Local Hamiltonians 局部哈密顿量中谱特征态的最大纠缠偏差

IEEE journal on selected areas in information theory Pub Date : 2024-10-31 DOI: 10.1109/JSAIT.2024.3487856

Yichen Huang

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Statistical Inference With Limited Memory: A Survey 记忆有限的统计推断：调查

IEEE journal on selected areas in information theory Pub Date : 2024-10-14 DOI: 10.1109/JSAIT.2024.3481296

Tomer Berg;Or Ordentlich;Ofer Shayevitz

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Tightening Continuity Bounds for Entropies and Bounds on Quantum Capacities 收紧熵的连续性约束和量子能力约束

IEEE journal on selected areas in information theory Pub Date : 2024-09-30 DOI: 10.1109/JSAIT.2024.3469929

Michael G. Jabbour;Nilanjana Datta

{"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}

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Dynamic Group Testing to Control and Monitor Disease Progression in a Population 控制和监测人群疾病进展的动态分组测试

IEEE journal on selected areas in information theory Pub Date : 2024-09-23 DOI: 10.1109/JSAIT.2024.3466649

Sundara Rajan Srinivasavaradhan;Pavlos Nikolopoulos;Christina Fragouli;Suhas Diggavi

{"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}

引用次数: 0