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Aggregating preferences under incomplete or constrained feedback is a fundamental problem in social choice and related domains. While prior work has established strong impossibility results for pairwise comparisons, this paper extends the…

Computer Science and Game Theory · Computer Science 2025-02-19 Evi Micha , Vasilis Varsamis

Fusions are a simple way of combining logics. For normal modal logics, fusions have been investigated in detail. In particular, it is known that, under certain conditions, decidability transfers from the component logics to their fusion.…

Artificial Intelligence · Computer Science 2011-06-10 F. Baader , C. Lutz , H. Sturm , F. Wolter

Composites, or linear combinations of variables, play an important role in multivariate behavioral research. They appear in the form of indices, inventories, formative constructs, parcels, and emergent variables. Although structural…

Methodology · Statistics 2025-09-03 Jörg Henseler , Xi Yu , Tamara Schamberger , Gregory R. Hancock , Florian Schuberth

Traditional models grounded in first principles often struggle with accuracy as the system's complexity increases. Conversely, machine learning approaches, while powerful, face challenges in interpretability and in handling physical…

Machine Learning · Computer Science 2024-01-31 Jessica Leoni , Valentina Breschi , Simone Formentin , Mara Tanelli

Predictive distributions need to be aggregated when probabilistic forecasts are merged, or when expert opinions expressed in terms of probability distributions are fused. We take a prediction space approach that applies to discrete, mixed…

Statistics Theory · Mathematics 2011-06-09 Tilmann Gneiting , Roopesh Ranjan

A causal, non-Hermitian, renormalizable, local, unitary and Lorentz convariant formulation of Quantum Theory (QT) (= Quantum Mechanics (QM) and Quantum Field Theory (QFT)) is developed which is free of formalistic problems we face in the…

High Energy Physics - Phenomenology · Physics 2011-07-19 F. Kleefeld

Combining p-values from independent statistical tests is a popular approach to meta-analysis, particularly when the data underlying the tests are either no longer available or are difficult to combine. A diverse range of p-value combination…

Methodology · Statistics 2017-12-15 Nicholas Heard , Patrick Rubin-Delanchy

Dependence logic provides an elegant approach for introducing dependencies between variables into the object language of first-order logic. In [1] generalized quantifiers were introduced in this context. However, a satisfactory account was…

Logic · Mathematics 2024-04-29 Fredrik Engström

Recent models for natural language understanding are inclined to exploit simple patterns in datasets, commonly known as shortcuts. These shortcuts hinge on spurious correlations between labels and latent features existing in the training…

Computation and Language · Computer Science 2024-11-19 Ukyo Honda , Tatsushi Oka , Peinan Zhang , Masato Mita

In this paper, we introduce a new learning strategy based on a seminal idea of Mojirsheibani (1999, 2000, 2002a, 2002b), who proposed a smart method for combining several classifiers, relying on a consensus notion. In many aggregation…

Machine Learning · Statistics 2018-03-09 Aurélie Fischer , Mathilde Mougeot

The problem of combining p-values is an old and fundamental one, and the classic assumption of independence is often violated or unverifiable in many applications. There are many well-known rules that can combine a set of arbitrarily…

Statistics Theory · Mathematics 2025-03-21 Matteo Gasparin , Ruodu Wang , Aaditya Ramdas

In many real-world settings, a decision-maker must combine information provided by different experts in order to decide on an effective policy. Alrajeh, Chockler, and Halpern [2018] showed how to combine causal models that are compatible in…

Artificial Intelligence · Computer Science 2020-05-21 Meir Friedenberg , Joseph Y. Halpern

Using proof-theoretic methods in the style of proof mining, we give novel computationally effective limit theorems for the convergence of the Cesaro-means of certain sequences of random variables. These results are intimately related to…

Probability · Mathematics 2024-06-28 Morenikeji Neri

The tension between qualitative theorizing and quantitative methods is pervasive in the social sciences, and poses a constant challenge to empirical research. But in science studies as an interdisciplinary specialty, there are additional…

Digital Libraries · Computer Science 2015-05-25 Loet Leydesdorff

Combinatorics is a powerful tool for dealing with relations among objectives mushroomed in the past century. However, an more important work for mathematician is to apply combinatorics to other mathematics and other sciences not merely to…

General Mathematics · Mathematics 2009-09-29 Linfan Mao

The categorical models of the differential lambda-calculus are additive categories because of the Leibniz rule which requires the summation of two expressions. This means that, as far as the differential lambda-calculus and differential…

Logic in Computer Science · Computer Science 2021-11-30 Thomas Ehrhard

In variable selection, a selection rule that prescribes the permissible sets of selected variables (called a "selection dictionary") is desirable due to the inherent structural constraints among the candidate variables. Such selection rules…

Methodology · Statistics 2024-01-17 Guanbo Wang , Mireille E. Schnitzer , Tom Chen , Rui Wang , Robert W. Platt

Making a decision is often a matter of listing and comparing positive and negative arguments. In such cases, the evaluation scale for decisions should be considered bipolar, that is, negative and positive values should be explicitly…

Artificial Intelligence · Computer Science 2014-01-16 Didier Dubois , Hélène Fargier , Jean-François Bonnefon

Coherent errors in quantum operations are ubiquitous. Whether arising from spurious environmental couplings or errors in control fields, such errors can accumulate rapidly and degrade the performance of a quantum circuit significantly more…

Quantum Physics · Physics 2022-05-03 Anthony M. Polloreno , Kevin C. Young

We explore the use of expert-guided bandit learning, which we refer to as online mixture-of-experts (OMoE). In this setting, given a context, a candidate committee of experts must determine how to aggregate their outputs to achieve optimal…

Machine Learning · Computer Science 2025-11-18 Larkin Liu , Jalal Etesami