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We study $\varepsilon$-stability in continuous logic. We first consider stability in a model, where we obtain a definability of types result with a better approximation than that in the literature. We also prove forking symmetry for…

Logic · Mathematics 2024-11-08 Nicolas Chavarria

The idea of fully accepting statements when the evidence has rendered them probable enough faces a number of difficulties. We leave the interpretation of probability largely open, but attempt to suggest a contextual approach to full belief.…

Artificial Intelligence · Computer Science 2013-02-08 Henry E. Kyburg

An algorithm for computing the stable model semantics of logic programs is developed. It is shown that one can extend the semantics and the algorithm to handle new and more expressive types of rules. Emphasis is placed on the use of…

Logic in Computer Science · Computer Science 2007-05-23 Patrik Simons

It has been widely acknowledged that probabilistic independence and logical independence cannot be coherently reconciled. By bridging these two notions, this paper addresses three long-standing problems that have puzzled the field of…

Probability · Mathematics 2026-05-07 Chuanfeng Sun

Transparency is a fundamental requirement for decision making systems when these should be deployed in the real world. It is usually achieved by providing explanations of the system's behavior. A prominent and intuitive type of explanations…

Machine Learning · Computer Science 2021-07-23 André Artelt , Valerie Vaquet , Riza Velioglu , Fabian Hinder , Johannes Brinkrolf , Malte Schilling , Barbara Hammer

We describe partial semi-simplicial resolutions of moduli spaces of surfaces with tangential structure. This allows us to prove a homological stability theorem for these moduli spaces, which often improves the known stability ranges and…

Algebraic Topology · Mathematics 2015-03-13 Oscar Randal-Williams

With their increase in performance, neural network architectures also become more complex, necessitating explainability. Therefore, many new and improved methods are currently emerging, which often generate so-called saliency maps in order…

Machine Learning · Computer Science 2024-12-24 Leonid Schwenke , Martin Atzmueller

The problem of binary hypothesis testing between two probability measures is considered. New sharp bounds are derived for the best achievable error probability of such tests based on independent and identically distributed observations.…

Information Theory · Computer Science 2024-05-30 Valentinian Lungu , Ioannis Kontoyiannis

To assess whether there is some signal in a big database, aggregate tests for the global null hypothesis of no effect are routinely applied in practice before more specialized analysis is carried out. Although a plethora of aggregate tests…

Statistics Theory · Mathematics 2024-05-08 Anders Bredahl Kock , David Preinerstorfer

It is well known that the resolution method (for propositional logic) is complete. However, completeness proofs found in the literature use an argument by contradiction showing that if a set of clauses is unsatisfiable, then it must have a…

Logic in Computer Science · Computer Science 2017-01-11 Jean Gallier

In Aristotelian logic, categorical propositions are divided in Universal Affirmative, Universal Negative, Particular Affirmative and Particular Negative. Possible relations between two of the mentioned type of propositions are encoded in…

Quantum Physics · Physics 2014-04-24 Hector Freytes , Christian de Ronde , Graciela Domenech

We study the binary hypothesis testing problem where an adversary may potentially corrupt a fraction of the samples. The detector is, however, permitted to abstain from making a decision if (and only if) the adversary is present. We…

Information Theory · Computer Science 2025-01-24 Malhar A. Managoli , K. R. Sahasranand , Vinod M. Prabhakaran

Scientific claims gain credibility by replicability, especially if replication under different circumstances and varying designs yields equivalent results. Aggregating results over multiple studies is, however, not straightforward, and when…

Methodology · Statistics 2023-12-27 Thom Benjamin Volker , Irene Klugkist

The algebraic properties of the combination of probabilistic choice and nondeterministic choice have long been a research topic in program semantics. This paper explains a formalization in the Coq proof assistant of a monad equipped with…

Logic in Computer Science · Computer Science 2023-12-12 Reynald Affeldt , Jacques Garrigue , David Nowak , Takafumi Saikawa

In a 1977 paper, Steffens identified an elegant criterion for determining when a countable graph has a perfect matching. In this paper, we will investigate the proof-theoretic strength of this result and related theorems. We show that a…

Logic · Mathematics 2020-06-23 Stephen Flood , Matthew Jura , Oscar Levin , Tyler Markkanen

In this article, we propose a one-sample test to check whether the support of the unknown distribution generating the data is homologically equivalent to the support of some specified distribution or not OR using the corresponding…

Methodology · Statistics 2023-12-01 Satish Kumar , Subhra Sankar Dhar

A central problem in proof-theory is that of finding criteria for identity of proofs, that is, for when two distinct formal derivations can be taken as denoting the same logical argument. In the literature one finds criteria which are…

Logic · Mathematics 2021-10-07 Paolo Pistone

We propose a "decomposition method" to prove non-asymptotic bound for the convergence of empirical measures in various dual norms. The main point is to show that if one measures convergence in duality with sufficiently regular observables,…

Probability · Mathematics 2018-02-13 Benoît Kloeckner

In this article, we propose some two-sample tests based on ball divergence and investigate their high dimensional behavior. First, we study their behavior for High Dimension, Low Sample Size (HDLSS) data, and under appropriate regularity…

Statistics Theory · Mathematics 2024-10-08 Bilol Banerjee , Anil K. Ghosh

Large language models (LLMs) are a promising venue for natural language understanding and generation tasks. However, current LLMs are far from reliable: they are prone to generate non-factual information and, more crucially, to contradict…

Machine Learning · Computer Science 2024-04-22 Diego Calanzone , Stefano Teso , Antonio Vergari