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A fundamental question in causal inference is whether it is possible to reliably infer manipulation effects from observational data. There are a variety of senses of asymptotic reliability in the statistical literature, among which the most…

Artificial Intelligence · Computer Science 2012-12-12 Jiji Zhang , Peter L. Spirtes

We study how to infer new choices from previous choices in a conservative manner. To make such inferences, we use the theory of choice functions: a unifying mathematical framework for conservative decision making that allows one to impose…

Artificial Intelligence · Computer Science 2020-07-16 Arne Decadt , Jasper De Bock , Gert de Cooman

In a recent work we have shown how to construct an information algebra of coherent sets of gambles defined on general possibility spaces. Here we analyze the connection of such an algebra with the set algebra of subsets of the possibility…

Logic in Computer Science · Computer Science 2021-05-28 Juerg Kohlas , Arianna Casanova , Marco Zaffalon

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that typically arise from applying decision rules…

Artificial Intelligence · Computer Science 2018-06-05 Jasper De Bock , Gert de Cooman

When conducting inference on partially identified parameters, confidence regions may cover the whole identified set with a prescribed probability, to which we will refer as set coverage, or they may cover each of its point with a prescribed…

Econometrics · Economics 2021-06-21 Marc Henry , Alexei Onatski

The classical concept of bounded completeness and its relation to sufficiency and ancillarity play a fundamental role in unbiased estimation, unbiased testing, and the validity of inference in the presence of nuisance parameters. In this…

Statistics Theory · Mathematics 2023-08-03 Marc Hallin , Bas Werker , Bo Zhou

Probabilistic programs are typically normal-looking programs describing posterior probability distributions. They intrinsically code up randomized algorithms and have long been at the heart of modern machine learning and approximate…

Programming Languages · Computer Science 2023-02-14 Lutz Klinkenberg , Tobias Winkler , Mingshuai Chen , Joost-Pieter Katoen

In this paper we formulate the problem of inference under incomplete information in very general terms. This includes modelling the process responsible for the incompleteness, which we call the incompleteness process. We allow the process…

Artificial Intelligence · Computer Science 2014-01-16 Marco Zaffalon , Enrique Miranda

Various semantics for studying the square of opposition and the hexagon of opposition have been proposed recently. We interpret sentences by imprecise (set-valued) probability assessments on a finite sequence of conditional events. We…

Probability · Mathematics 2017-10-13 Niki Pfeifer , Giuseppe Sanfilippo

A relatively new topic in computability theory is the study of notions of computation that are robust against mistakes on some kind of small set. However, despite the recent popularity of this topic relatively foundational questions about…

Logic · Mathematics 2025-08-12 Peter M. Gerdes

Factual consistency is one of important summary evaluation dimensions, especially as summary generation becomes more fluent and coherent. The ESTIME measure, recently proposed specifically for factual consistency, achieves high correlations…

Computation and Language · Computer Science 2022-01-10 Oleg Vasilyev , John Bohannon

We argue that Godel's completeness theorem is equivalent to completability of consistent theories, and Godel's incompleteness theorem is equivalent to the fact that this completion is not constructive, in the sense that there are some…

Logic · Mathematics 2019-07-02 Saeed Salehi

Prediction, where observed data is used to quantify uncertainty about a future observation, is a fundamental problem in statistics. Prediction sets with coverage probability guarantees are a common solution, but these do not provide…

Statistics Theory · Mathematics 2022-11-22 Leonardo Cella , Ryan Martin

Coherence is an essential property of well-written texts, that refers to the way textual units relate to one another. In the era of generative AI, coherence assessment is essential for many NLP tasks; summarization, generation, long-form…

Computation and Language · Computer Science 2024-08-14 Aviya Maimon , Reut Tsarfaty

This article reviews and develops an epistemological tradition in the philosophy of science, known as convergentism, which holds that inference methods should be assessed based on their ability to converge to the truth across a range of…

Other Statistics · Statistics 2025-07-01 Hanti Lin

Providing natural language explanations for recommendations is particularly useful from the perspective of a non-expert user. Although several methods for providing such explanations have recently been proposed, we argue that an important…

Computation and Language · Computer Science 2025-03-19 Jakub Raczyński , Mateusz Lango , Jerzy Stefanowski

A subjective expected utility policy making centre, managing complex, dynamic systems, needs to draw on the expertise of a variety of disparate panels of experts and integrate this information coherently. To achieve this, diverse supporting…

Methodology · Statistics 2015-12-21 Jim Q. Smith , Martine J. Barons , Manuele Leonelli

In this work, we develop a formal system of inductive logic. It uses an infinitary language that allows for countable conjunctions and disjunctions. It is based on a set of nine syntactic rules of inductive inference, and contains classical…

Probability · Mathematics 2025-05-01 Jason Swanson

This article presents a new argument against many forms of moral and prudential value incompleteness. The argument relies on two central principles: (i) a weak "negative dominance" principle, to the effect that Lottery 1 is better than…

Theoretical Economics · Economics 2026-04-21 Christian Tarsney , Harvey Lederman , Dean Spears

This article focuses on the importance of the precise calculation of similarity factors between papers and reviewers for performing a fair and accurate automatic assignment of reviewers to papers. It suggests that papers and reviewers'…

Information Retrieval · Computer Science 2013-09-26 Yordan Kalmukov