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This paper shows that sequential statistical analysis techniques can be generalised to the problem of selecting between alternative forecasting methods using scoring rules. A return to basic principles is necessary in order to show that…

Statistics Theory · Mathematics 2025-05-15 David T. Frazier , Donald S. Poskitt

There has been a lot of interest recently in proving lower bounds on the size of linear programs needed to represent a given polytope P. In a breakthrough paper Fiorini et al. [Proceedings of 44th ACM Symposium on Theory of Computing 2012,…

Optimization and Control · Mathematics 2013-11-12 Hamza Fawzi , Pablo A. Parrilo

We develop a proof-theoretic semantics (P-tS) for second-order logic (S-oL), providing an inferentialist alternative to both full and Henkin model-theoretic interpretations. Our approach is grounded in base-extension semantics (B-eS), a…

Logic · Mathematics 2025-08-12 Alexander V. Gheorghiu , David J. Pym

We prove that the existence of finite combinatorial objects such as affine planes, mutually orthogonal Latin squares, and resolvable balanced incomplete block designs can be reformulated as the existence of certain algorithmic reductions…

Combinatorics · Mathematics 2026-04-21 Damir D. Dzhafarov , Jun le Goh

We introduce a novel, logic-independent framework for the study of sequent-style proof systems, which covers a number of proof-theoretic formalisms and concrete proof systems that appear in the literature. In particular, we introduce a…

Logic in Computer Science · Computer Science 2025-12-22 Tim S. Lyon , Piotr Ostropolski-Nalewaja

We study cutoff results for parameterized verification and synthesis of guarded protocols, as introduced by Emerson and Kahlon (2000). Guarded protocols describe systems of processes whose transitions are enabled or disabled depending on…

Logic in Computer Science · Computer Science 2017-07-06 Swen Jacobs , Mouhammad Sakr

The Stochastic Extragradient (SEG) method is one of the most popular algorithms for solving min-max optimization and variational inequalities problems (VIP) appearing in various machine learning tasks. However, several important questions…

Optimization and Control · Mathematics 2022-02-23 Eduard Gorbunov , Hugo Berard , Gauthier Gidel , Nicolas Loizou

We study the problem of bounding the posterior distribution of discrete probabilistic programs with unbounded support, loops, and conditioning. Loops pose the main difficulty in this setting: even if exact Bayesian inference is possible,…

Programming Languages · Computer Science 2024-12-06 Fabian Zaiser , Andrzej S. Murawski , C. -H. Luke Ong

A small minimal k-blocking set B in PG(n, q), q = pt, p prime, is a set of less than 3(qk + 1)/2 points in PG(n, q), such that every (n - k)-dimensional space contains at least one point of B and such that no proper subset of B satisfies…

Combinatorics · Mathematics 2012-01-17 Geertrui Van de Voorde

Stopping sets play a crucial role in failure events of iterative decoders over a binary erasure channel (BEC). The $\ell$-th stopping redundancy is the minimum number of rows in the parity-check matrix of a code, which contains no stopping…

Information Theory · Computer Science 2018-10-02 Yauhen Yakimenka , Vitaly Skachek , Irina E. Bocharova , Boris D. Kudryashov

Error-correcting codes enable reliable communication, yet practical soft decoding remains challenging across code families and block lengths. We propose SB-ECC, a score-based decoder that casts decoding as continuous-time denoising. A…

Machine Learning · Computer Science 2026-05-28 Alon Helvits , Eliya Nachmani

We give a sharpened form of Siegel Lemma's w. r. t. the maximum norm. This implies a new lower bound on the greatest element of a sum-distinct set of positive integers (Erd\"os-Moser problem). The main tools are Minkowski's theorem on…

Number Theory · Mathematics 2007-05-23 Iskander Aliev

In this paper, we present an elementary proof of the Bhatia-\v{S}emrl Theorem, utilizing the Minimax Theorem for bounded linear operators by Asplund and Ptak [1]. Some related results are also discussed.

Functional Analysis · Mathematics 2025-03-20 Hranislav Stanković

In this paper, we study the structure of set-multilinear arithmetic circuits and set-multilinear branching programs with the aim of showing lower bound results. We define some natural restrictions of these models for which we are able to…

Computational Complexity · Computer Science 2015-11-10 V. Arvind , S. Raja

The AWGNC, BSC, and max-fractional pseudocodeword redundancy of a code is defined as the smallest number of rows in a parity-check matrix such that the corresponding minimum pseudoweight is equal to the minimum Hamming distance of the code.…

Information Theory · Computer Science 2010-05-20 Jens Zumbragel , Mark F. Flanagan , Vitaly Skachek

We show that for constraint satisfaction problems (CSPs), sub-exponential size linear programming relaxations are as powerful as $n^{\Omega(1)}$-rounds of the Sherali-Adams linear programming hierarchy. As a corollary, we obtain…

Computational Complexity · Computer Science 2018-01-03 Pravesh K. Kothari , Raghu Meka , Prasad Raghavendra

Concurrent systems are notoriously difficult to analyze, and technological advances such as weak memory architectures greatly compound this problem. This has renewed interest in partial order semantics as a theoretical foundation for formal…

Logic in Computer Science · Computer Science 2015-04-02 Alex Horn , Daniel Kroening

We study a new class of NP search problems, those which can be proved total using standard combinatorial reasoning based on approximate counting. Our model for this kind of reasoning is the bounded arithmetic theory $\mathrm{APC}_2$ of…

Logic · Mathematics 2021-11-29 Leszek Aleksander Kołodziejczyk , Neil Thapen

An important question concerning contextualized word embedding (CWE) models like BERT is how well they can represent different word senses, especially those in the long tail of uncommon senses. Rather than build a WSD system as in previous…

Computation and Language · Computer Science 2021-09-22 Luke Gessler , Nathan Schneider

Nogood learning is a powerful approach to reducing search in Constraint Programming (CP) solvers. The current state of the art, called Lazy Clause Generation (LCG), uses resolution to derive nogoods expressing the reasons for each search…

Artificial Intelligence · Computer Science 2013-06-20 Geoffrey Chu , Peter J. Stuckey
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