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Quantum information theory studies the fundamental limits that physical laws impose on information processing tasks such as data compression and data transmission on noisy channels. This thesis presents general techniques that allow one to…

Quantum Physics · Physics 2010-04-13 Frédéric Dupuis

In this paper, a possibilistic disjunctive logic programming approach for modeling uncertain, incomplete and inconsistent information is defined. This approach introduces the use of possibilistic disjunctive clauses which are able to…

Artificial Intelligence · Computer Science 2015-03-19 Juan Carlos Nieves , Mauricio Osorio , Ulises Cortés

This paper presents a soundness and completeness proof for propositional intuitionistic calculus with respect to the semantics of computability logic. The latter interprets formulas as interactive computational problems, formalized as games…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

The problem of sequentially maximizing the expectation of a function seeks to maximize the expected value of a function of interest without having direct control on its features. Instead, the distribution of such features depends on a given…

Machine Learning · Statistics 2022-10-26 Diego Martinez-Taboada , Dino Sejdinovic

We study the tractability of conjunctive query answering for queries with unbounded arity. It is well known that tractability of the problem can be characterised in terms of the queries treewidth under the assumption of bounded arity. We…

Databases · Computer Science 2022-06-14 Matthias Lanzinger

These lectures deal with the problem of inductive inference, that is, the problem of reasoning under conditions of incomplete information. Is there a general method for handling uncertainty? Or, at least, are there rules that could in…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Ariel Caticha

Open-world query answering is the problem of deciding, given a set of facts, conjunction of constraints, and query, whether the facts and constraints imply the query. This amounts to reasoning over all instances that include the facts and…

Logic in Computer Science · Computer Science 2016-07-19 Antoine Amarilli , Michael Benedikt

Warning: This paper contains a mistake, rendering the proof of the main theorem invalid. The logic of Bunched Implications (BI) combines both additive and multiplicative connectives, which include two primitive intuitionistic implications.…

Logic in Computer Science · Computer Science 2024-04-15 Alexander Gheorghiu , Simon Docherty , David Pym

Information theory is a mathematical theory of learning with deep connections with topics as diverse as artificial intelligence, statistical physics, and biological evolution. Many primers on information theory paint a broad picture with…

Information Theory · Computer Science 2019-03-26 Philip Chodrow

To explain conceptual gap between classical/quantum and other, hypothetical descriptions of world, several principles has been proposed. So far, all these principles have not explicitly included the uncertainty relation. Here we introduce…

Quantum Physics · Physics 2017-02-22 L. Czekaj , M. Horodecki , P. Horodecki , R. Horodecki

During the past decade, there has been an extensive investigation of the computational complexity of the consistent answers of Boolean conjunctive queries under primary key constraints. Much of this investigation has focused on…

Databases · Computer Science 2015-03-03 Foto N. Afrati , Phokion G. Kolaitis , Angelos Vasilakopoulos

When additional information sources are available, an important question for an agent solving a certain problem is how to optimally use the information the sources are capable of providing. A framework that relates information accuracy on…

Data Analysis, Statistics and Probability · Physics 2013-01-11 Eugene Perevalov , David Grace

We consider here the problem of obtaining reliable, consistent information from inconsistent databases -- databases that do not have to satisfy given integrity constraints. We use the notion of consistent query answer -- a query answer…

Databases · Computer Science 2007-05-23 Jan Chomicki , Jerzy Marcinkowski

Open-world query answering is the problem of deciding, given a set of facts, conjunction of constraints, and query, whether the facts and constraints imply the query. This amounts to reasoning over all instances that include the facts and…

Logic in Computer Science · Computer Science 2020-03-06 Antoine Amarilli , Michael Benedikt

For a first-order theory $T$, the Constraint Satisfaction Problem of $T$ is the computational problem of deciding whether a given conjunction of atomic formulas is satisfiable in some model of $T$. In this article we develop sufficient…

Logic · Mathematics 2020-12-03 Manuel Bodirsky , Johannes Greiner

Algorithms of inference in a computer system oriented to input and semantic processing of text information are presented. Such inference is necessary for logical questions when the direct comparison of objects from a question and database…

Computation and Language · Computer Science 2012-02-02 Yuriy Ostapov

Knowledge gradient is a design principle for developing Bayesian sequential sampling policies to solve optimization problems. In this paper we consider the ranking and selection problem in the presence of covariates, where the best…

Statistics Theory · Mathematics 2022-01-17 Liang Ding , L. Jeff Hong , Haihui Shen , Xiaowei Zhang

When a relational database is queried, the result is normally a relation. Some queries, however, only require a yes/no answer; such queries are often called boolean queries. It is customary in database theory to express boolean queries by…

Databases · Computer Science 2019-03-04 Dimitri Surinx , Jan Van den Bussche

This paper examines two related problems that are central to developing an autonomous decision-making agent, such as a robot. Both problems require generating structured representafions from a database of unstructured declarative knowledge…

Artificial Intelligence · Computer Science 2013-04-10 Spencer Star

Information theory provides tools to predict the performance of a learning algorithm on a given dataset. For instance, the accuracy of learning an unknown parameter can be upper bounded by reducing the learning task to hypothesis testing…

Quantum Physics · Physics 2026-04-21 Evan Peters
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