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Variational inequalities are an important tool, which includes minimization, saddles, games, fixed-point problems. Modern large-scale and computationally expensive practical applications make distributed methods for solving these problems…

Optimization and Control · Mathematics 2023-03-01 Aleksandr Beznosikov , Alexander Gasnikov

We consider the problem of successive-refinement coding for lossy compression of individual sequences, namely, compression in two stages, where in the first stage, a coarse description at a relatively low rate is sent from the encoder to…

Information Theory · Computer Science 2025-02-25 Neri Merhav

Reductions combine collections of input values with an associative and often commutative operator to produce collections of results. When the same input value contributes to multiple outputs, there is an opportunity to reuse partial…

Programming Languages · Computer Science 2024-12-19 Louis Narmour , Tomofumi Yuki , Sanjay Rajopadhye

Latent variable models have been successfully applied in lossless compression with the bits-back coding algorithm. However, bits-back suffers from an increase in the bitrate equal to the KL divergence between the approximate posterior and…

The reliability of erasure-coded distributed storage systems, as measured by the mean time to data loss (MTTDL), depends on the repair bandwidth of the code. Repair-efficient codes provide reliability values several orders of magnitude…

Information Theory · Computer Science 2017-08-04 Vaneet Aggarwal , Chao Tian , Vinay A. Vaishampayan , Yih-Farn R. Chen

In this paper we wish to introduce a method to reconstruct large size Welch Bound Equality (WBE) codes from small size WBE codes. The advantage of these codes is that the implementation of ML decoder for the large size codes is reduced to…

Information Theory · Computer Science 2009-03-07 Mohammad Javad Faraji , Pedram Pad , Farokh Marvasti

Sampling-based Model Predictive Control (MPC) is a flexible control framework that can reason about non-smooth dynamics and cost functions. Recently, significant work has focused on the use of machine learning to improve the performance of…

Robotics · Computer Science 2022-12-07 Jacob Sacks , Byron Boots

The interleaving distance is arguably the most prominent distance measure in topological data analysis. In this paper, we provide bounds on the computational complexity of determining the interleaving distance in several settings. We show…

Computational Geometry · Computer Science 2018-05-01 Håvard Bakke Bjerkevik , Magnus Bakke Botnan

Measuring software complexity plays an important role to meet the demands of complex software. The cyclomatic complexity is one of most used and renowned metric among the other three proposed and researched metrics that are namely: Line of…

Software Engineering · Computer Science 2014-12-22 Ankita Garg

Coded distributed computing (CDC) is a new technique proposed with the purpose of decreasing the intense data exchange required for parallelizing distributed computing systems. Under the famous MapReduce paradigm, this coded approach has…

Information Theory · Computer Science 2022-06-28 Federico Brunero , Petros Elia

Data storage systems are more reliable than their individual components. In order to build highly reliable systems out of less reliable parts, systems introduce redundancy. In replicated systems, objects are simply copied several times with…

Information Theory · Computer Science 2013-08-13 John Cook , Robert Primmer , Ab de Kwant

Retrieving data from large-scale source code archives is vital for AI training, neural-based software analysis, and information retrieval, to cite a few. This paper studies and experiments with the design of a compressed key-value store for…

Data Structures and Algorithms · Computer Science 2026-01-21 Paolo Ferragina , Francesco Tosoni

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant…

Machine Learning · Computer Science 2023-09-26 Giorgos Bouritsas , Andreas Loukas , Nikolaos Karalias , Michael M. Bronstein

Coded caching is a recently proposed technique for dealing with large scale content distribution over the Internet. As in conventional caching, it leverages the presence of local caches at the end users. However, it considers coding in the…

Information Theory · Computer Science 2016-05-06 Li Tang , Aditya Ramamoorthy

Background: Transitioning from an old medical coding system to a new one can be challenging, especially when the two coding systems are significantly different. The US experienced such a transition in 2015. Objective: This research aims to…

Information Theory · Computer Science 2020-12-24 Jerome Niyirora

We study how much a linear program (LP) can be compressed when solved repeatedly, given prior knowledge about its objective function. Existing data-driven projection methods learn low-dimensional surrogate LPs with approximate…

Optimization and Control · Mathematics 2026-05-26 Yuhan Ye , Omar Bennouna

This paper presents and analyzes a novel concatenated coding scheme for enabling error resilience in two distributed storage settings: one being storage using existing regenerating codes and the second being storage using locally repairable…

Information Theory · Computer Science 2013-12-12 Natalia Silberstein , Ankit Singh Rawat , Sriram Vishwanath

We raise the question of approximating the compressibility of a string with respect to a fixed compression scheme, in sublinear time. We study this question in detail for two popular lossless compression schemes: run-length encoding (RLE)…

Data Structures and Algorithms · Computer Science 2007-06-11 Sofya Raskhodnikova , Dana Ron , Ronitt Rubinfeld , Adam Smith

This paper considers the Gaussian multiple-access channel (MAC) in the asymptotic regime where the number of users grows linearly with the code length. We propose efficient coding schemes based on random linear models with approximate…

Information Theory · Computer Science 2022-05-04 Kuan Hsieh , Cynthia Rush , Ramji Venkataramanan

Despite the exceptional performance of multi-modal large language models (MLLMs), their deployment requires substantial computational resources. Once malicious users induce high energy consumption and latency time (energy-latency cost), it…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Kuofeng Gao , Jindong Gu , Yang Bai , Shu-Tao Xia , Philip Torr , Wei Liu , Zhifeng Li
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