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Demixing is the problem of identifying multiple structured signals from a superimposed, undersampled, and noisy observation. This work analyzes a general framework, based on convex optimization, for solving demixing problems. When the…

Information Theory · Computer Science 2013-10-01 Michael B. McCoy , Joel A. Tropp

In this paper, we investigate the leader election problem in diameter-two networks. Recently, Chatterjee et al. [DC 2020] studied the leader election in diameter-two networks. They presented a $O(\log n)$-round deterministic {implicit}…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-23 Manish Kumar , Anisur Rahaman Molla , Sumathi Sivasubramaniam

An influential 1990 paper of Hochbaum and Shanthikumar made it common wisdom that "convex separable optimization is not much harder than linear optimization" [JACM 1990]. We exhibit two fundamental classes of mixed integer (linear) programs…

Discrete Mathematics · Computer Science 2021-11-17 Cornelius Brand , Martin Koutecký , Alexandra Lassota , Sebastian Ordyniak

We illustrate how computer-aided methods can be used to investigate the fundamental limits of the caching systems, which are significantly different from the conventional analytical approach usually seen in the information theory…

Information Theory · Computer Science 2018-08-28 Chao Tian

Stream fairness, fairness between all streams in the system, is a more restrictive condition than sub-stream fairness, fairness between all streams of each user. Thus sub-stream fairness alleviates utility loss as well as complexity and…

Information Theory · Computer Science 2016-11-17 Cenk M. Yetis , Yong Zeng , Kushal Anand , Yong Liang Guan , Erry Gunawan

The performance of convolutional codes decoding by the Viterbi algorithm should not depend on the particular distribution of zeros and ones in the input messages, as they are linear. However, it was identified that specific implementations…

Information Theory · Computer Science 2015-10-06 Alexey Shapin , Denis Kleyko , Nikita Lyamin , Evgeny Osipov , Oleg Melentyev

Score-based methods, such as diffusion models and Bayesian inverse problems, are often interpreted as learning the data distribution in the low-noise limit ($\sigma \to 0$). In this work, we propose an alternative perspective: their success…

Machine Learning · Statistics 2026-03-17 Xiang Li , Zebang Shen , Ya-Ping Hsieh , Niao He

Rate and diversity impose a fundamental trade-off in communications. This trade-off was investigated for flat-fading channels in [15] as well as for Inter-symbol Interference (ISI) channels in [1]. A different point of view was explored in…

Information Theory · Computer Science 2009-12-24 S. Dusad , S. N. Diggavi

We consider the notions of agreement, diversity, and polarization in ordinal elections (that is, in elections where voters rank the candidates). While (computational) social choice offers good measures of agreement between the voters, such…

Computer Science and Game Theory · Computer Science 2023-05-18 Piotr Faliszewski , Andrzej Kaczmarczyk , Krzysztof Sornat , Stanisław Szufa , Tomasz Wąs

When selecting a subset of candidates (a so-called committee) based on the preferences of voters, proportional representation is often a major desideratum. When going beyond simplistic models such as party-list or district-based elections,…

Computer Science and Game Theory · Computer Science 2023-02-07 Markus Brill , Jannik Peters

Matching mechanisms play a central role in operations management across diverse fields including education, healthcare, and online platforms. However, experimentally comparing a new matching algorithm against a status quo presents some…

Methodology · Statistics 2026-01-30 Chonghuan Wang

Neural networks and other machine learning models compute continuous representations, while humans communicate with discrete symbols. Reconciling these two forms of communication is desirable to generate human-readable interpretations or to…

Machine Learning · Computer Science 2021-04-05 André F. T. Martins

Linear and semidefinite programming (LP, SDP), regularisation through basis pursuit (BP) and Lasso have seen great success in mathematics, statistics, data science, computer-assisted proofs and learning. The success of LP is traditionally…

Optimization and Control · Mathematics 2022-08-03 Alexander Bastounis , Anders C Hansen , Verner Vlačić

We give the first approximation algorithm for mixed packing and covering semidefinite programs (SDPs) with polylogarithmic dependence on width. Mixed packing and covering SDPs constitute a fundamental algorithmic primitive with recent…

Data Structures and Algorithms · Computer Science 2021-07-13 Arun Jambulapati , Yin Tat Lee , Jerry Li , Swati Padmanabhan , Kevin Tian

We consider the problem of super-resolving the line spectrum of a multisinusoidal signal from a finite number of samples, some of which may be completely corrupted. Measurements of this form can be modeled as an additive mixture of a…

Optimization and Control · Mathematics 2017-03-23 Carlos Fernandez-Granda , Gongguo Tang , Xiaodong Wang , Le Zheng

We consider synchronous dynamic networks which like radio networks may have asymmetric communication links, and are affected by communication rather than processor failures. In this paper we investigate the minimal message survivability in…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-03-29 Yehuda Afek , Eli Gafni

We recently showed in [1] the superiority of certain structured coding matrices ensembles (such as partial row-orthogonal) for sparse superposition codes when compared with purely random matrices with i.i.d. entries, both…

Information Theory · Computer Science 2022-07-12 YuHao Liu , Teng Fu , Jean Barbier , TianQi Hou

We address the Leader Election (LE) problem in networks of anonymous sensors sharing no kind of common coordinate system. Leader Election is a fundamental symmetry breaking problem in distributed computing. Its goal is to assign value 1…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-02-22 Yoann dieudonné , Florence Levé , Franck Petit , Vincent Villain

Indistinguishable objects often occur when modelling problems in constraint programming, as well as in other related paradigms. They occur when objects can be viewed as being drawn from a set of unlabelled objects, and the only operation…

Artificial Intelligence · Computer Science 2025-03-24 Ozgur Akgun , Mun See Chang , Ian P. Gent , Christopher Jefferson

We introduce a sub-symmetry of a differential system as an infinitesimal transformation of a subset of the system that leaves the subset invariant on the solution set of the entire system. We discuss the geometrical meaning and properties…

Mathematical Physics · Physics 2017-05-03 V. Rosenhaus , Ravi Shankar
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