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Consider a distributed coding for computing problem with constant decoding locality, i.e., with a vanishing error probability, any single sample of the function can be approximately recovered by probing only constant number of compressed…

Information Theory · Computer Science 2024-03-01 Deheng Yuan , Tao Guo , Zhongyi Huang , Shi Jin

The optimal coding scheme for communicating a Gaussian message over an Additive White Gaussian noise (AWGN) channel with AWGN output feedback, with a limited number of transmissions is unknown. Even if we restrict the scope of the coding…

Information Theory · Computer Science 2022-05-24 Rajesh Mishra , Deepanshu Vasal , Hyeji Kim

The design of communication systems dedicated to machine learning tasks is one key aspect of goal-oriented communications. In this framework, this article investigates the interplay between data reconstruction and learning from the same…

Information Theory · Computer Science 2024-04-30 Jiahui Wei , Elsa Dupraz , Philippe Mary

Consider a pair of correlated Gaussian sources (X1,X2). Two separate encoders observe the two components and communicate compressed versions of their observations to a common decoder. The decoder is interested in reconstructing a linear…

Information Theory · Computer Science 2007-07-25 D. Krithivasan , S. S. Pradhan

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

Quadratic optimization problems (QPs) are ubiquitous, and solution algorithms have matured to a reliable technology. However, the precision of solutions is usually limited due to the underlying floating-point operations. This may cause…

Optimization and Control · Mathematics 2019-08-20 Tobias Weber , Sebastian Sager , Ambros Gleixner

In this paper, we revisit the discrete lossy Gray-Wyner problem. In particular, we derive its optimal second-order coding rate region, its error exponent (reliability function) and its moderate deviations constant under mild conditions on…

Information Theory · Computer Science 2017-01-05 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

We consider the distributed source coding system for $L$ correlated Gaussian observations $Y_i, i=1,2, ..., L$. Let $X_i,i=1,2, ..., L$ be $L$ correlated Gaussian random variables and $N_i,$ $i=1,2,... L$ be independent additive Gaussian…

Information Theory · Computer Science 2009-08-09 Yasutada Oohama

We consider a variation of the Wyner-Ziv problem pertaining to lossy compression of individual sequences using finite-state encoders and decoders. There are two main results in this paper. The first characterizes the relationship between…

Information Theory · Computer Science 2007-07-13 Neri Merhav , Jacob Ziv

This paper studies the possibilities made open by the use of Lazy Clause Generation (LCG) based approaches to Constraint Programming (CP) for tackling sequential classical planning. We propose a novel CP model based on seminal ideas on…

Artificial Intelligence · Computer Science 2023-07-18 Anubhav Singh , Miquel Ramirez , Nir Lipovetzky , Peter J. Stuckey

Wyner's common information was originally defined for a pair of dependent discrete random variables. Its significance is largely reflected in, hence also confined to, several existing interpretations in various source coding problems. This…

Information Theory · Computer Science 2013-01-11 Ge Xu , Wei Liu , Biao Chen

We derive the optimal second-order coding region and moderate deviations constant for successive refinement source coding with a joint excess-distortion probability constraint. We consider two scenarios: (i) a discrete memoryless source…

Information Theory · Computer Science 2016-08-29 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

The problem of reliable transmission of correlated sources over the broadcast channel, originally studied by Han and Costa, is revisited. An alternative characterization of their sufficient condition for reliable transmission is given,…

Information Theory · Computer Science 2009-12-22 Paolo Minero , Young-Han Kim

We consider the following communication scenario. An encoder causally observes the Wiener process and decides when and what to transmit about it. A decoder makes real-time estimation of the process using causally received codewords. We…

Information Theory · Computer Science 2020-05-15 Nian Guo , Victoria Kostina

Distributed storage systems with replication are well known for storing large amount of data. A large number of replication is done in order to provide reliability. This makes the system expensive. Various methods have been proposed over…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-01 Mit Sheth , Krishna Gopal Benerjee , Manish K. Gupta

A large amount of recent research has the far-reaching goal of finding training methods for deep neural networks that can serve as alternatives to backpropagation (BP). A prominent example is predictive coding (PC), which is a…

Machine Learning · Computer Science 2022-11-08 Luca Pinchetti , Tommaso Salvatori , Yordan Yordanov , Beren Millidge , Yuhang Song , Thomas Lukasiewicz

In this paper, we propose an efficient coding scheme for the binary Chief Executive Officer (CEO) problem under logarithmic loss criterion. Courtade and Weissman obtained the exact rate-distortion bound for a two-link binary CEO problem…

Information Theory · Computer Science 2018-01-04 Mahdi Nangir , Reza Asvadi , Mahmoud Ahmadian-Attari , Jun Chen

In successive refinement of information, the decoder refines its representation of the source progressively as it receives more encoded bits. The rate-distortion region of successive refinement describes the minimum rates required to attain…

Information Theory · Computer Science 2018-11-22 Victoria Kostina , Ertem Tuncel

Generative models have attracted significant interest due to their ability to handle uncertainty by learning the inherent data distributions. However, two prominent generative models, namely Generative Adversarial Networks (GANs) and…

Machine Learning · Computer Science 2023-04-25 Yu Wang , Zhiwei Liu , Liangwei Yang , Philip S. Yu

The challenge of constructing feedback control laws for risk-averse optimal control of partial differential equations (PDEs) with random coefficients is addressed. The control objective composes a tracking-type cost with the nonlinear…

Optimization and Control · Mathematics 2025-08-22 Philipp A. Guth , Karl Kunisch
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