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Computational preference elicitation methods are tools used to learn people's preferences quantitatively in a given context. Recent works on preference elicitation advocate for active learning as an efficient method to iteratively construct…

Human-Computer Interaction · Computer Science 2024-07-29 Vijay Keswani , Vincent Conitzer , Hoda Heidari , Jana Schaich Borg , Walter Sinnott-Armstrong

We study preferences estimated from finite choice experiments and provide sufficient conditions for convergence to a unique underlying "true" preference. Our conditions are weak, and therefore valid in a wide range of economic environments.…

Theoretical Economics · Economics 2020-11-03 Christopher P. Chambers , Federico Echenique , Nicolas Lambert

The choice of admissible trading strategies in mathematical modelling of financial markets is a delicate issue, going back to Harrison and Kreps (1979). In the context of optimal portfolio selection with expected utility preferences this…

Computational Finance · Quantitative Finance 2017-07-25 Sara Biagini , Aleš Černý

We propose a simple yet effective solution to tackle the often-competing goals of fairness and utility in classification tasks. While fairness ensures that the model's predictions are unbiased and do not discriminate against any particular…

Machine Learning · Computer Science 2023-08-16 Anique Tahir , Lu Cheng , Huan Liu

Our objective is to extend the standard results of preservation and reflection of properties by bisimulations to the coalgebraic setting, as well as to study under what conditions these results hold for simulations. The notion of…

Logic in Computer Science · Computer Science 2024-02-05 Ignacio Fábregas , Miguel Palomino , David de Frutos-Escrig

Two fundamental axioms in social choice theory are consistency with respect to a variable electorate and consistency with respect to components of similar alternatives. In the context of traditional non-probabilistic social choice, these…

Computer Science and Game Theory · Computer Science 2016-07-15 Florian Brandl , Felix Brandt , Hans Georg Seedig

The traditional calculus-based introduction to statistical inference consists of a semester of probability followed by a semester of frequentist inference. Cobb (2015) challenges the statistical education community to rethink the…

Other Statistics · Statistics 2020-07-09 Jim Albert

Philosophers now seem to agree that frequentism is an untenable strategy to explain the meaning of probabilities. Nevertheless, I want to revive frequentism, and I will do so by grounding probabilities on typicality in the same way as the…

History and Philosophy of Physics · Physics 2021-01-05 Mario Hubert

We analyse preference inference, through consistency, for general preference languages based on lexicographic models. We identify a property, which we call strong compositionality, that applies for many natural kinds of preference…

Logic in Computer Science · Computer Science 2024-11-01 Nic Wilson , Anne-Marie George

Axiomatizing mathematical structures is a goal of Mathematical Logic. Axiomatizability of the theories of some structures have turned out to be quite difficult and challenging, and some remain open. However axiomatization of some…

Logic · Mathematics 2021-11-30 Saeed Salehi

Some criticisms that have been raised against the Cox approach to probability theory are addressed. Should we use a single real number to measure a degree of rational belief? Can beliefs be compared? Are the Cox axioms obvious? Are there…

Data Analysis, Statistics and Probability · Physics 2015-05-14 Ariel Caticha

Gambles are random variables that model possible changes in monetary wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes.…

Economics · Quantitative Finance 2016-02-03 Ole Peters , Murray Gell-Mann

A primary motivation for reasoning under uncertainty is to derive decisions in the face of inconclusive evidence. However, Shafer's theory of belief functions, which explicitly represents the underconstrained nature of many reasoning…

Artificial Intelligence · Computer Science 2013-04-08 Thomas M. Strat

Proof search has been used to specify a wide range of computation systems. In order to build a framework for reasoning about such specifications, we make use of a sequent calculus involving induction and co-induction. These proof principles…

Logic in Computer Science · Computer Science 2009-09-30 Alwen Tiu , Alberto Momigliano

We give a survey of the foundations of statistical queries and their many applications to other areas. We introduce the model, give the main definitions, and we explore the fundamental theory statistical queries and how how it connects to…

Machine Learning · Computer Science 2020-05-15 Lev Reyzin

Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack of data renders learning a probability distribution for the problem impractical. The first…

Statistics Theory · Mathematics 2026-05-11 Fabio Cuzzolin

A classical portfolio theory deals with finding the optimal proportion in which an agent invests a wealth in a risk-free asset and a probabilistic risky asset. Formulating and solving the problem depend on how the risk is represented and…

Portfolio Management · Quantitative Finance 2019-01-28 Irina Georgescu , Jani Kinnunen

By probabilistic logic I mean a normative theory of belief that explains how a body of evidence affects one's degree of belief in a possible hypothesis. A new axiomatization of such a theory is presented which avoids a finite additivity…

Artificial Intelligence · Computer Science 2013-04-10 Romas Aleliunas

The famous Afriat's theorem from the theory of revealed preferences establishes necessary and suffient conditions for existence of utility function for a given set of choices and prices. The result on existence of a {\it homogeneous}…

Optimization and Control · Mathematics 2014-05-27 Alexander V. Kolesnikov , Olga V. Kudryavtseva , Tigran Nagapetyan

One purpose -- quite a few thinkers would say the main purpose -- of seeking knowledge about the world is to enhance our ability to make good decisions. An item of knowledge that can make no conceivable difference with regard to anything we…

Artificial Intelligence · Computer Science 2013-04-12 Henry E. Kyburg
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