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In this paper, we propose a lattice-based robust distributed source coding system for two correlated sources and provide a detailed performance analysis under the high resolution assumption. It is shown, among other things, that, in the…

Information Theory · Computer Science 2018-10-04 Dania Elzouki , Sorina Dumitrescu , Jun Chen

Massive data analysis calls for distributed algorithms and theories. We design a multi-round distributed algorithm for canonical correlation analysis. We construct principal directions through the convex formulation of canonical correlation…

Computation · Statistics 2024-12-24 Canyi Chen , Liping Zhu

Let $X_1, ..., X_m$ be a set of $m$ statistically dependent sources over the common alphabet $\mathbb{F}_q$, that are linearly independent when considered as functions over the sample space. We consider a distributed function computation…

Information Theory · Computer Science 2016-11-17 V. Lalitha , N. Prakash , K. Vinodh , P. Vijay Kumar , S. Sandeep Pradhan

Symmetric multilevel diversity coding (SMDC) is a source coding problem where the independent sources are ordered according to their importance. It was shown that separately encoding independent sources (referred to as…

Information Theory · Computer Science 2024-01-29 Tao Guo , Laigang Guo , Yinfei Xu , Congduan Li , Shi Jin , Raymond Yeung

The reliability function of variable-rate Slepian-Wolf coding is linked to the reliability function of channel coding with constant composition codes, through which computable lower and upper bounds are derived. The bounds coincide at rates…

Information Theory · Computer Science 2016-08-08 Jun Chen , Da-ke He , Ashish Jagmohan , Luis A. Lastras-Montaño

This paper deals with a coding problem called complementary delivery, where messages from two correlated sources are jointly encoded and each decoder reproduces one of two messages using the other message as the side information. Both…

Information Theory · Computer Science 2008-02-13 Shigeaki Kuzuoka , Akisato Kimura , Tomohiko Uyematsu

Optimal zero-delay coding (quantization) of $\mathbb{R}^d$-valued linearly generated Markov sources is studied under quadratic distortion. The structure and existence of deterministic and stationary coding policies that are optimal for the…

Information Theory · Computer Science 2022-01-17 Meysam Ghomi , Tamas Linder , Serdar Yuksel

Coded distributed computation has become common practice for performing gradient descent on large datasets to mitigate stragglers and other faults. This paper proposes a novel algorithm that encodes the partial derivatives themselves and…

Machine Learning · Computer Science 2022-06-22 Pedro Soto , Ilia Ilmer , Haibin Guan , Jun Li

This paper investigates a unification of distributed source coding, multiple description coding, and source coding with side information at decoders. The equivalence between the multiple-decoder extension of distributed source coding with…

Information Theory · Computer Science 2024-10-28 Jun Muramatsu

We present a decode-and-forward transmission scheme based on spatially-coupled low-density parity-check (SC-LDPC) codes for a network consisting of two (possibly correlated) sources, one relay, and one destination. The links between the…

Information Theory · Computer Science 2014-02-17 Stefan Schwandter , Alexandre Graell i Amat , Gerald Matz

In this paper, we study distributed stochastic optimization to minimize a sum of smooth and strongly-convex local cost functions over a network of agents, communicating over a strongly-connected graph. Assuming that each agent has access to…

Machine Learning · Computer Science 2019-04-11 Ran Xin , Anit Kumar Sahu , Usman A. Khan , Soummya Kar

This paper establishes the rate region for a class of source coding function computation setups where sources of information are available at the nodes of a tree and where a function of these sources must be computed at the root. The rate…

Information Theory · Computer Science 2015-04-08 Milad Sefidgaran , Aslan Tchamkerten

Consider a lossy compression system with $\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under…

Information Theory · Computer Science 2018-07-19 Yizhong Wang , Li Xie , Xuan Zhang , Jun Chen

Clustering performs an essential role in many real world applications, such as market research, pattern recognition, data analysis, and image processing. However, due to the high dimensionality of the input feature values, the data being…

Machine Learning · Computer Science 2021-02-16 Si Lu , Ruisi Li

The Distributed Constraint Optimization Problem (DCOP) formulation is a powerful tool to model cooperative multi-agent problems that need to be solved distributively. A core assumption of existing approaches is that DCOP solutions can be…

Artificial Intelligence · Computer Science 2025-02-21 Ben Rachmut , Stylianos Loukas Vasileiou , Nimrod Meir Weinstein , Roie Zivan , William Yeoh

Cooperative optimization is a new way for finding global optima of complicated functions of many variables. It has some important properties not possessed by any conventional optimization methods. It has been successfully applied in solving…

Information Theory · Computer Science 2007-07-13 Xiaofei Huang

Diffusion models over discrete spaces have recently shown striking empirical success, yet their theoretical foundations remain incomplete. In this paper, we study the sampling efficiency of score-based discrete diffusion models under a…

Machine Learning · Computer Science 2026-02-17 Daniil Dmitriev , Zhihan Huang , Yuting Wei

We present a joint source-channel multiple description (JSC-MD) framework for resource-constrained network communications (e.g., sensor networks), in which one or many deprived encoders communicate a Markov source against bit errors and…

Information Theory · Computer Science 2007-08-28 Xiaolin Wu , Xiaohan Wang , Zhe Wang

Distributed algorithms for both discrete-time and continuous-time linearly solvable optimal control (LSOC) problems of networked multi-agent systems (MASs) are investigated in this paper. A distributed framework is proposed to partition the…

Machine Learning · Computer Science 2021-02-19 Neng Wan , Aditya Gahlawat , Naira Hovakimyan , Evangelos A. Theodorou , Petros G. Voulgaris

Distributed computing systems are well-known to suffer from the problem of slow or failed nodes; these are referred to as stragglers. Straggler mitigation (for distributed matrix computations) has recently been investigated from the…

Information Theory · Computer Science 2024-12-20 Anindya Bijoy Das , Aditya Ramamoorthy