Zobrazeno 1 - 10
of 177
pro vyhledávání: '"BENAVOLI, ALESSIO"'
Autor:
Benavoli, Alessio, Azzimonti, Dario
Preference modelling lies at the intersection of economics, decision theory, machine learning and statistics. By understanding individuals' preferences and how they make choices, we can build products that closely match their expectations, paving the
Externí odkaz:
http://arxiv.org/abs/2403.11782
Exchangeability is a fundamental concept in probability theory and statistics. It allows to model situations where the order of observations does not matter. The classical de Finetti's theorem provides a representation of infinitely exchangeable sequ
Externí odkaz:
http://arxiv.org/abs/2306.03869
In consumer theory, ranking available objects by means of preference relations yields the most common description of individual choices. However, preference-based models assume that individuals: (1) give their preferences only between pairs of object
Externí odkaz:
http://arxiv.org/abs/2302.00406
Contemporary undertakings provide limitless opportunities for widespread application of machine reasoning and artificial intelligence in situations characterised by uncertainty, hostility and sheer volume of data. The paper develops a valuation netwo
Externí odkaz:
http://arxiv.org/abs/2208.02443
We introduce a formulation of quantum theory (QT) as a general probabilistic theory but expressed via quasi-expectation operators (QEOs). This formulation provides a direct interpretation of density matrices as quasi-moment matrices. Using QEOs, we w
Externí odkaz:
http://arxiv.org/abs/2203.04124
Gaussian processes (GPs) are an important tool in machine learning and statistics with applications ranging from social and natural science through engineering. They constitute a powerful kernelized non-parametric method with well-calibrated uncertai
Externí odkaz:
http://arxiv.org/abs/2112.09519
In this work we introduce a new framework for multi-objective Bayesian optimisation where the multi-objective functions can only be accessed via choice judgements, such as ``I pick options A,B,C among this set of five options A,B,C,D,E''. The fact th
Externí odkaz:
http://arxiv.org/abs/2110.08217
We present a two-stage Metropolis-Hastings algorithm for sampling probabilistic models, whose log-likelihood is computationally expensive to evaluate, by using a surrogate Gaussian Process (GP) model. The key feature of the approach, and the differen
Externí odkaz:
http://arxiv.org/abs/2109.13891
Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing
Bayesian optimization (BO) is an approach to globally optimizing black-box objective functions that are expensive to evaluate. BO-powered experimental design has found wide application in materials science, chemistry, experimental physics, drug devel
Externí odkaz:
http://arxiv.org/abs/2107.12809
Two particles are identical if all their intrinsic properties, such as spin and charge, are the same, meaning that no quantum experiment can distinguish them. In addition to the well known principles of quantum mechanics, understanding systems of ide
Externí odkaz:
http://arxiv.org/abs/2105.04336