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The estimation of categorical distributions under marginal constraints summarizing some sample from a population in the most-generalizable way is key for many machine-learning and data-driven approaches. We provide a parameter-agnostic…

High Energy Physics - Theory · Physics 2023-11-17 Orestis Loukas , Ho Ryun Chung

We propose a new algorithm for minimal unsatisfiable core extraction, based on a deeper exploration of resolution-refutation properties. We provide experimental results on formal verification benchmarks confirming that our algorithm finds…

Logic in Computer Science · Computer Science 2020-06-11 Nachum Dershowitz , Ziyad Hanna , Alexander Nadel

We show an essentially tight bound on the number of adaptively chosen statistical queries that a computationally efficient algorithm can answer accurately given $n$ samples from an unknown distribution. A statistical query asks for the…

Cryptography and Security · Computer Science 2015-02-23 Thomas Steinke , Jonathan Ullman

We address the problem of producing a lower bound for the mean of a discrete probability distribution, with known support over a finite set of real numbers, from an iid sample of that distribution. Up to a constant, this is equivalent to…

Statistics Theory · Mathematics 2025-02-25 Erik Learned-Miller

Physical Unclonable Functions (PUFs) exploit variations in the manufacturing process to derive bit sequences from integrated circuits, which can be used as secure cryptographic keys. Instead of storing the keys in an insecure, non-volatile…

Information Theory · Computer Science 2018-01-11 Sven Müelich , Sven Puchinger , Martin Bossert

The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible while constrained to match empirically estimated feature expectations. However, in many real-world…

Machine Learning · Computer Science 2022-08-16 Kenneth Bogert , Yikang Gui , Prashant Doshi

We study an entropic optimal transport problem in which the transport plan is penalized by a nonlinear convex functional acting on the coupling. We establish existence, uniqueness, and uniform a priori bounds for minimizers, and we show…

Optimization and Control · Mathematics 2025-12-15 Anna Kazeykina , Zhenjie Ren , Xiaozhen Wang , Yufei Zhang

We study fundamental block-structured integer programs called tree-fold and multi-stage IPs. Tree-fold IPs admit a constraint matrix with independent blocks linked together by few constraints in a recursive pattern; and transposing their…

Computational Complexity · Computer Science 2024-02-28 Christoph Hunkenschröder , Kim-Manuel Klein , Martin Koutecký , Alexandra Lassota , Asaf Levin

We study the minimax identity for a non-decreasing upper-semicontinuous utility function satisfying mild growth assumption. In contrast to the classical setting, we do not impose the assumption that the utility function is concave. By…

Probability · Mathematics 2022-07-12 Olena Bahchedjioglou , Georgiy Shevchenko

We consider a setting where we have a ground set $M$ together with real-valued set functions $f_1, \dots, f_n$, and the goal is to partition $M$ into two sets $S_1,S_2$ such that $|f_i(S_1) - f_i(S_2)|$ is small for every $i$. Many results…

Combinatorics · Mathematics 2025-10-01 Alexandros Hollender , Pasin Manurangsi , Raghu Meka , Warut Suksompong

Efficiency criteria for conformal prediction, such as \emph{observed fuzziness} (i.e., the sum of p-values associated with false labels), are commonly used to \emph{evaluate} the performance of given conformal predictors. Here, we…

Machine Learning · Computer Science 2020-05-15 Nicolo Colombo , Vladimir Vovk

This paper considers the linear objective function optimization with respect to a novel system of fuzzy relation equations, where the fuzzy compositions are defined by the minimum t-norm. It is proved that the feasible solution set is…

Optimization and Control · Mathematics 2023-09-22 Amin Ghodousian , Mahdi Mollakazemiha

In this paper we provide a method to obtain tight lower bounds on the minimum redundancy achievable by a Huffman code when the probability distribution underlying an alphabet is only partially known. In particular, we address the case where…

Information Theory · Computer Science 2019-09-04 Ian Blanes , Miguel Hernández-Cabronero , Joan Serra-Sagristà , Michael W. Marcellin

For any pair $(X,Z)$ of correlated random variables we can think of $Z$ as a randomized function of $X$. Provided that $Z$ is short, one can make this function computationally efficient by allowing it to be only approximately correct. In…

Cryptography and Security · Computer Science 2016-07-18 Maciej Skorski

Motivated by the entropy computations relevant to the evaluation of decrease in entropy in bit reset operations, the authors investigate the deficit in an entropic inequality involving two independent random variables, one continuous and…

Information Theory · Computer Science 2018-09-21 James Melbourne , Saurav Talukdar , Shreyas Bhaban , Murti V. Salapaka

For a sample of Exponentially distributed durations we aim at point estimation and a confidence interval for its parameter. A duration is only observed if it has ended within a certain time interval, determined by a Uniform distribution.…

Methodology · Statistics 2021-10-19 Rafael Weißbach , Dominik Wied

We study the maximum achievable differential entropy at the output of a system assigning to each input X the sum X+N, with N a given noise with probability law absolutely continuous with respect to the Lebesgue measure and where the input…

Optimization and Control · Mathematics 2016-02-04 Francisco J. Piera

Surface incompressibility, also called inextensibility, imposes a zero-surface-divergence constraint on the velocity of a closed deformable material surface. The well-posedness of the mechanical problem under such constraint depends on an…

Numerical Analysis · Mathematics 2015-07-28 Gustavo C. Buscaglia

We expand on previous work involving "vacuum-bounded" states, i.e., states such that every measurement performed outside a specified interior region gives the same result as in the vacuum. We improve our previous techniques by removing the…

High Energy Physics - Theory · Physics 2009-10-30 Ken D. Olum

This paper addresses a problem of estimating an additive functional given $n$ i.i.d. samples drawn from a discrete distribution $P=(p_1,...,p_k)$ with alphabet size $k$. The additive functional is defined as…

Information Theory · Computer Science 2018-12-04 Kazuto Fukuchi , Jun Sakuma