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We study adversarial binary hypothesis testing under memory constraints. The test is a time-invariant randomized finite state machine (FSM) with S states. Associated with each hypothesis is a set of distributions. Given the hypothesis, the…

Information Theory · Computer Science 2026-05-13 Malhar A. Managoli , Vinod M. Prabhakaran

We consider a problem of simple hypothesis testing using a randomized test via a tunable loss function proposed by Liao \textit{et al}. In this problem, we derive results that correspond to the Neyman--Pearson lemma, the Chernoff--Stein…

Information Theory · Computer Science 2022-08-30 Akira Kamatsuka

Consider the problem of distributed binary hypothesis testing with two terminals, where the decision is made at one of them (the "receiver"). We study the exponent of the error probability of the second type. Previously, an achievable…

Information Theory · Computer Science 2025-08-26 Yuval Kochman , Ligong Wang

We study the adversarial binary hypothesis testing problem in the sequential setting. Associated with each hypothesis is a closed, convex set of distributions. Given the hypothesis, each observation is generated according to a distribution…

Information Theory · Computer Science 2025-11-14 Eeshan Modak , Mayank Bakshi , Bikash Kumar Dey , Vinod M. Prabhakaran

A detection system with a single sensor and two detectors is considered, where each of the terminals observes a memoryless source sequence, the sensor sends a message to both detectors and the first detector sends a message to the second…

Information Theory · Computer Science 2018-10-09 Pierre Escamilla , Abdellatif Zaidi , Michèle Wigger

Consider a distributed detection problem in which the underlying distributions of the observations are unknown; instead of these distributions, noisy versions of empirically observed statistics are available to the fusion center. These…

Information Theory · Computer Science 2020-02-13 Haiyun He , Lin Zhou , Vincent Y. F. Tan

We study the problem of communication over a compound quantum channel in the presence of entanglement. Classically such channels are modeled as a collection of conditional probability distributions wherein neither the sender nor the…

Quantum Physics · Physics 2019-03-19 Anurag Anshu , Rahul Jain , Naqueeb Ahmad Warsi

A collaborative distributed binary decision problem is considered. Two statisticians are required to declare the correct probability measure of two jointly distributed memoryless process, denoted by $X^n=(X_1,\dots,X_n)$ and…

Information Theory · Computer Science 2016-04-11 Gil Katz , Pablo Piantanida , Merouane Debbah

We consider the problem of distributed binary hypothesis testing of two sequences that are generated by an i.i.d. doubly-binary symmetric source. Each sequence is observed by a different terminal. The two hypotheses correspond to different…

Information Theory · Computer Science 2018-01-03 Eli Haim , Yuval Kochman

A detection system with a single sensor and $\mathsf{K}$ detectors is considered, where each of the terminals observes a memoryless source sequence and the sensor sends a common message to all the detectors. The communication of this…

Information Theory · Computer Science 2018-05-17 Pierre Escamilla , Michèle Wigger , Abdellatif Zaidi

We consider symmetric hypothesis testing in quantum statistics, where the hypotheses are density operators on a finite-dimensional complex Hilbert space, representing states of a finite quantum system. We prove a lower bound on the…

Quantum Physics · Physics 2009-04-30 Michael Nussbaum , Arleta Szkoła

Coding and testing schemes for binary hypothesis testing over noisy networks are proposed and their corresponding type-II error exponents are derived. When communication is over a discrete memoryless channel (DMC), our scheme combines…

Information Theory · Computer Science 2018-06-15 Sadaf Salehkalaibar , Michele Wigger

In this paper, we study a model of communication under adversarial noise. In this model, the adversary makes online decisions on whether to corrupt a transmitted bit based on only the value of that bit. Like the usual binary symmetric…

Information Theory · Computer Science 2014-01-21 Arya Mazumdar

We study binary hypothesis testing for i.i.d. observations under a multiplicative context weight. For the optimal weighted total loss, defined as the sum of weighted type-I and type-II losses, we prove the logarithmic asymptotic $$ L_n^* =…

Statistics Theory · Mathematics 2026-05-12 Mark Kelbert , El'mira Yu. Kalimulina

This paper identifies the Stein-exponent of distributed detection when the sensor communicates to the decision center over a discrete memoryless channel (DMC) subject to one of three stringent communication constraints: 1) The number of…

Information Theory · Computer Science 2026-01-14 Abdelaziz Bounhar , Mireille Sarkiss , Michèle Wigger

Consider a countably infinite set of nodes, which sequentially make decisions between two given hypotheses. Each node takes a measurement of the underlying truth, observes the decisions from some immediate predecessors, and makes a decision…

Information Theory · Computer Science 2015-06-12 Zhenliang Zhang , Edwin K. P. Chong , Ali Pezeshki , William Moran

We study the problem of mismatched binary hypothesis testing between i.i.d. distributions. We analyze the tradeoff between the pairwise error probability exponents when the actual distributions generating the observation are different from…

Information Theory · Computer Science 2022-04-28 Parham Boroumand , Albert Guillén i Fàbregas

The distributed hypothesis testing problem with full side-information is studied. The trade-off (reliability function) between the two types of error exponents under limited rate is studied in the following way. First, the problem is…

Information Theory · Computer Science 2019-04-24 Nir Weinberger , Yuval Kochman

We investigate the problem of reliable communication in the presence of active adversaries that can tamper with the transmitted data. We consider a legitimate transmitter-receiver pair connected over multiple communication paths (routes).…

Information Theory · Computer Science 2014-04-28 Mahtab Mirmohseni , Panagiotis Papadimitratos

Identification of latent binary sequences from a pool of noisy observations has a wide range of applications in both statistical learning and population genetics. Each observed sequence is the result of passing one of the latent…

Statistics Theory · Mathematics 2018-11-28 Khashayar Gatmiry , Seyed Abolfazl Motahari