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A number of writers(Joseph Halpern and Fahiem Bacchus among them) have offered semantics for formal languages in which inferences concerning probabilities can be made. Our concern is different. This paper provides a formalization of…

Artificial Intelligence · Computer Science 2013-03-25 Henry E. Kyburg

Generating a huge number of association rules reduces their utility in the decision making process, done by domain experts. In this context, based on the theory of Formal Concept Analysis, we propose to extend the notion of Formal Concept…

Databases · Computer Science 2012-09-19 Wafa Tebourski Ourida Ben Boubaker Saidi

There is much interest in providing probabilistic semantics for defaults but most approaches seem to suffer from one of two problems: either they require numbers, a problem defaults were intended to avoid, or they generate peculiar side…

Artificial Intelligence · Computer Science 2013-04-10 Eric Neufeld , David L Poole

Theories of natural language and concepts have been unable to model the flexibility, creativity, context-dependence, and emergence, exhibited by words, concepts and their combinations. The mathematical formalism of quantum theory has…

Artificial Intelligence · Computer Science 2016-09-09 Diederik Aerts , Jan Broekaert , Liane Gabora , Sandro Sozzo

Conceptual combination performs a fundamental role in creating the broad range of compound phrases utilized in everyday language. This article provides a novel probabilistic framework for assessing whether the semantics of conceptual…

Computation and Language · Computer Science 2014-11-24 Peter D. Bruza , Kirsty Kitto , Brentyn J. Ramm , Laurianne Sitbon

A convenient framework for dealing with asymptotic limit problems of probabilistic nature is provided. These problems include questions such as finding the asymptotic proportion of terms of a sequence falling inside a given interval, or the…

History and Overview · Mathematics 2024-04-08 Michaël Bensimhoun

In the paper I study properties of random polynomials with respect to a general system of functions. Some lower bounds for the mathematical expectation of the uniform and recently introduced integral-uniform norms of random polynomials are…

Probability · Mathematics 2007-05-23 Pavel Grigoriev

Implicit probabilistic models are models defined naturally in terms of a sampling procedure and often induces a likelihood function that cannot be expressed explicitly. We develop a simple method for estimating parameters in implicit models…

Machine Learning · Computer Science 2018-10-23 Ke Li , Jitendra Malik

The present paper proposes a novel way to unify Rough Set Theory and Formal Concept Analysis. Our method stems from results and insights developed in the algebraic theory of modal logic, and is based on the idea that Pawlak's original…

Based on rectangle theory of formal concept and set covering theory, the concept reduction preserving binary relations is investigated in this paper. It is known that there are three types of formal concepts: core concepts, relative…

Artificial Intelligence · Computer Science 2021-11-02 Jianqin Zhou , Sichun Yang , Xifeng Wang , Wanquan Liu

Abstract argumentation offers an appealing way of representing and evaluating arguments and counterarguments. This approach can be enhanced by a probability assignment to each argument. There are various interpretations that can be ascribed…

Artificial Intelligence · Computer Science 2014-05-15 Anthony Hunter , Matthias Thimm

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

Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can potentially discover a broad range of themes in a data set,…

Artificial Intelligence · Computer Science 2008-08-08 Chaitanya Chemudugunta , Padhraic Smyth , Mark Steyvers

We introduce the notions of topological entropy of a formal language and of a topological automaton. We show that the entropy function is surjective and bound the entropy of languages accepted by deterministic {\epsilon}-free push-down…

Formal Languages and Automata Theory · Computer Science 2019-04-25 Florian Starke

A standard informal method for analyzing the asymptotic complexity of a program is to extract a recurrence that describes its cost in terms of the size of its input, and then to compute a closed-form upper bound on that recurrence. We give…

Programming Languages · Computer Science 2022-08-09 Norman Danner , Daniel R. Licata

A formalism is presented to obtain closed evolution equations for asymptotic probability distribution functions of turbulence magnitudes. The formalism is derived for a generic evolution equation, so that the final result can be easily…

Fluid Dynamics · Physics 2007-06-25 F. O. Minotti , E. Speranza

Natural language semantics has recently sought to combine the complementary strengths of formal and distributional approaches to meaning. More specifically, proposals have been put forward to augment formal semantic machinery with…

Computation and Language · Computer Science 2021-03-03 Noortje J. Venhuizen , Petra Hendriks , Matthew W. Crocker , Harm Brouwer

Topological models of empirical and formal inquiry are increasingly prevalent. They have emerged in such diverse fields as domain theory [1, 16], formal learning theory [18], epistemology and philosophy of science [10, 15, 8, 9, 2],…

Machine Learning · Computer Science 2017-08-01 Konstantin Genin , Kevin T. Kelly

Ontological models are attempts to quantitatively describe the results of a probabilistic theory, such as Quantum Mechanics, in a framework exhibiting an explicit realism-based underpinning. Unlike either the well known quasi-probability…

Quantum Physics · Physics 2008-07-02 Nicholas Harrigan , Terry Rudolph , Scott Aaronson

In this paper we propose a general approach to define a many-valued preferential interpretation of gradual argumentation semantics. The approach allows for conditional reasoning over arguments and boolean combination of arguments, with…

Artificial Intelligence · Computer Science 2025-06-10 Mario Alviano , Laura Giordano , Daniele Theseider Dupré
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