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A large body of research is currently investigating on the connection between machine learning and game theory. In this work, game theory notions are injected into a preference learning framework. Specifically, a preference learning problem…

Machine Learning · Computer Science 2018-12-20 Mirko Polato , Fabio Aiolli

Standard methods for aligning large language models with human preferences learn from pairwise comparisons among sampled candidate responses and regularize toward a reference policy. Despite their effectiveness, the effects of sampling and…

Machine Learning · Computer Science 2026-02-13 Yurong Chen , Yu He , Michael I. Jordan , Fan Yao

Different from most conventional recommendation problems, sequential recommendation focuses on learning users' preferences by exploiting the internal order and dependency among the interacted items, which has received significant attention…

Information Retrieval · Computer Science 2025-03-14 Liwei Pan , Weike Pan , Meiyan Wei , Hongzhi Yin , Zhong Ming

We analyse strategic, complete information, sequential voting with ordinal preferences over the alternatives. We consider several voting mechanisms: plurality voting and approval voting with deterministic or uniform tie-breaking rules. We…

Computer Science and Game Theory · Computer Science 2019-04-19 Oren Dean , Yakov Babichenko , Moshe Tennenholtz

Observations on the past provide some hints about what will happen in the future, and this can be quantified using information theory. The ``predictive information'' defined in this way has connections to measures of complexity that have…

Statistical Mechanics · Physics 2007-05-23 William Bialek , Naftali Tishby

The continuous evolution of cities poses significant challenges in terms of managing and understanding their complex dynamics. With the increasing demand for transparency and the growing availability of open urban data, it has become…

Databases · Computer Science 2024-09-10 Jey Puget Gil , Emmanuel Coquery , John Samuel , Gilles Gesquiere

Information Retrieval (IR) aims at retrieving documents that are most relevant to a query provided by a user. Traditional techniques rely mostly on syntactic methods. In some cases, however, links at a deeper semantic level must be…

Artificial Intelligence · Computer Science 2020-02-19 Marcello Balduccini , Emily LeBlanc

One of the core advantages topological methods for data analysis provide is that the language of (co)chains can be mapped onto the semantics of the data, providing a natural avenue for human understanding of the results. Here, we describe…

Other Statistics · Statistics 2019-04-30 Chad Giusti , Darrick Lee

For a computational system to be intelligent, it should be able to perform, at least, basic deductions. Nonetheless, since deductions are, in some sense, equivalent to tautologies, it seems that they do not provide new information. The…

Logic in Computer Science · Computer Science 2014-04-21 Anderson de Araújo

We establish an equivalence between two seemingly different theories: one is the traditional axiomatisation of incomplete preferences on horse lotteries based on the mixture independence axiom; the other is the theory of desirable gambles…

Artificial Intelligence · Computer Science 2018-01-03 Marco Zaffalon , Enrique Miranda

An expression for the coefficients of a linear iterative equation in terms of the parameters of the source equation is given both for equations in standard form and for equations in reduced normal form. The operator generating an iterative…

Classical Analysis and ODEs · Mathematics 2012-07-31 J. C. Ndogmo , F. M. Mahomed

The note derives an expression for the number of interchanges made by selection sort when the sorting elements are iid variates from geometric distribution. Empirical results reveal we can work with a simpler model compared to what is…

Computation · Statistics 2012-02-28 Debasish Sahani , Soubhik Chakraborty

A mechanism is proposed that allows to interpret the temporal evolution of a physical system as a result of the inability of an observer to record its whole state and a simple example is given. It is based on a review of the concepts of…

General Physics · Physics 2010-10-15 Alberto Bicego

Preference Inference involves inferring additional user preferences from elicited or observed preferences, based on assumptions regarding the form of the user's preference relation. In this paper we consider a situation in which…

Logic in Computer Science · Computer Science 2024-09-18 Nic Wilson , Anne-Marie George , Barry O'Sullivan

Recent literature highlights the advantages of implementing social rules via dynamic game forms. We characterize when truth-telling remains a dominant strategy in gradual mechanisms implementing strategy-proof social rules, where agents…

Theoretical Economics · Economics 2025-03-27 Wenqian Wang , Zhiwen Zheng

This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms…

Information Theory · Computer Science 2013-04-05 Carlos Gershenson

Probabilistic cellular automata with deterministic updating are quantum systems. We employ the quantum formalism for an investigation of random probabilistic cellular automata, which start with a probability distribution over initial…

Quantum Physics · Physics 2024-05-17 A. Kreuzkamp , C. Wetterich

When trying to solve a computational problem, we are often faced with a choice between algorithms that are guaranteed to return the right answer but differ in their runtime distributions (e.g., SAT solvers, sorting algorithms). This paper…

Artificial Intelligence · Computer Science 2023-06-06 Devon R. Graham , Kevin Leyton-Brown , Tim Roughgarden

Preference queries are relational algebra or SQL queries that contain occurrences of the winnow operator ("find the most preferred tuples in a given relation"). Such queries are parameterized by specific preference relations. Semantic…

Databases · Computer Science 2007-05-23 Jan Chomicki

The iterative development process is a framework used to design products and applications across a wide range of domains. It centers around building prototypes, testing them, and updating based on the test results. We discuss how we applied…

Other Computer Science · Computer Science 2024-05-09 Christopher R. H. Hanusa , Eric Vergo
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