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A distributed binary hypothesis testing (HT) problem involving two parties, a remote observer and a detector, is studied. The remote observer has access to a discrete memoryless source, and communicates its observations to the detector via…

Information Theory · Computer Science 2020-04-30 Sreejith Sreekumar , Asaf Cohen , Deniz Gündüz

We study distribution testing with communication and memory constraints in the following computational models: (1) The {\em one-pass streaming model} where the goal is to minimize the sample complexity of the protocol subject to a memory…

Machine Learning · Computer Science 2019-06-12 Ilias Diakonikolas , Themis Gouleakis , Daniel M. Kane , Sankeerth Rao

The classical communication complexity of testing closeness of discrete distributions has recently been studied by Andoni, Malkin and Nosatzki (ICALP'19). In this problem, two players each receive $t$ samples from one distribution over…

Computational Complexity · Computer Science 2023-12-29 Aleksandrs Belovs , Arturo Castellanos , François Le Gall , Guillaume Malod , Alexander A. Sherstov

In this paper, we study a distributed learning problem constrained by constant communication bits. Specifically, we consider the distributed hypothesis testing (DHT) problem where two distributed nodes are constrained to transmit a constant…

Information Theory · Computer Science 2022-01-25 Xiangxiang Xu , Shao-Lun Huang

We revisit the distributed hypothesis testing (or hypothesis testing with communication constraints) problem from the viewpoint of privacy. Instead of observing the raw data directly, the transmitter observes a sanitized or randomized…

Information Theory · Computer Science 2019-06-26 Atefeh Gilani , Selma Belhadj Amor , Sadaf Salehkalaibar , Vincent Y. F. Tan

We study the scalability of consensus-based distributed optimization algorithms by considering two questions: How many processors should we use for a given problem, and how often should they communicate when communication is not free?…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-09-06 Konstantinos I. Tsianos , Sean Lawlor , Michael G. Rabbat

We study the fundamental limits to communication-efficient distributed methods for convex learning and optimization, under different assumptions on the information available to individual machines, and the types of functions considered. We…

Machine Learning · Computer Science 2015-10-29 Yossi Arjevani , Ohad Shamir

In this paper we obtain some bounds on communication complexity of Gap Hamming Distance problem ($\mathsf{GHD}^n_{L, U}$): Alice and Bob are given binary string of length $n$ and they are guaranteed that Hamming distance between their…

Computational Complexity · Computer Science 2015-12-02 Alexander Kozachinskiy

A number of problems in communication systems demand the distributed allocation of network resources in order to provide better services, sampling and distribution methods. The solution to these issues is becoming more challenging due to…

Statistical Mechanics · Physics 2007-05-23 Pablo Echenique , Jesus Gomez-Gardenes , Yamir Moreno , Alexei Vazquez

In the distributed triangle detection problem, we have an $n$-vertex network $G=(V,E)$ with one player for each vertex of the graph who sees the edges incident on the vertex. The players communicate in synchronous rounds using the edges of…

Data Structures and Algorithms · Computer Science 2025-08-14 Sepehr Assadi , Janani Sundaresan

In this paper we consider a network of processors aiming at cooperatively solving linear programming problems subject to uncertainty. Each node only knows a common cost function and its local uncertain constraint set. We propose a…

Optimization and Control · Mathematics 2019-08-27 Mohammadreza Chamanbaz , Giuseppe Notarstefano , Roland Bouffanais

This work studies distributed learning in the spirit of Yao's model of communication complexity: consider a two-party setting, where each of the players gets a list of labelled examples and they communicate in order to jointly perform some…

Machine Learning · Computer Science 2018-04-24 Daniel M. Kane , Roi Livni , Shay Moran , Amir Yehudayoff

In distributed learning, the goal is to perform a learning task over data distributed across multiple nodes with minimal (expensive) communication. Prior work (Daume III et al., 2012) proposes a general model that bounds the communication…

Machine Learning · Computer Science 2012-04-17 Hal Daume , Jeff M. Phillips , Avishek Saha , Suresh Venkatasubramanian

Balliu et al. (DISC 2020) classified the hardness of solving binary labeling problems with distributed graph algorithms; in these problems the task is to select a subset of edges in a $2$-colored tree in which white nodes of degree $d$ and…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-20 Henrik Lievonen , Timothé Picavet , Jukka Suomela

We consider the problem of the classical simulation of quantum measurements in the scenario of communication complexity. Regev and Toner (2007) have presented a 2-bit protocol which simulates one particular correlation function arising from…

Quantum Physics · Physics 2013-10-09 Adrian Kosowski , Marcin Markiewicz

We consider the problem of estimating the arithmetic average of a finite collection of real vectors stored in a distributed fashion across several compute nodes subject to a communication budget constraint. Our analysis does not rely on any…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-24 Jakub Konečný , Peter Richtárik

A distributed binary hypothesis testing problem, in which multiple observers transmit their observations to a detector over noisy channels, is studied. Given its own side information, the goal of the detector is to decide between two…

Information Theory · Computer Science 2017-04-06 Sreejith Sreekumar , Deniz Gündüz

To reproduce in a local hidden variables theory correlations that violate Bell inequalities, communication must occur between the parties. We show that the amount of violation of a Bell inequality imposes a lower bound on the average…

Quantum Physics · Physics 2007-10-22 Stefano Pironio

The communication complexity of many fundamental problems reduces greatly when the communicating parties share randomness that is independent of the inputs to the communication task. Natural communication processes (say between humans)…

Computational Complexity · Computer Science 2024-01-24 Clément L. Canonne , Venkatesan Guruswami , Raghu Meka , Madhu Sudan

Quantum communication leads to strong correlations, that can outperform classical ones. Complementary to previous works in this area, we investigate correlations in prepare-and-measure scenarios assuming a bound on the information content…