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We propose a new approach to promote safety in classification tasks with established concepts. Our approach -- called a conceptual safeguard -- acts as a verification layer for models that predict a target outcome by first predicting the…

Machine Learning · Computer Science 2024-11-08 Hailey Joren , Charles Marx , Berk Ustun

In this paper an approach to automated deduction under uncertainty,based on possibilistic logic, is proposed ; for that purpose we deal with clauses weighted by a degree which is a lower bound of a necessity or a possibility measure,…

Artificial Intelligence · Computer Science 2013-04-08 Didier Dubois , Jerome Lang , Henri Prade

Addressing the large inefficiencies generated by the Deferred Acceptance (DA) mechanism requires priority violations, but which ones are justifiable? The leading approach is to ask individuals if they consent to waive their priority…

Theoretical Economics · Economics 2026-04-09 Josué Ortega , R. Pablo Arribillaga

We study the problem of contextual combinatorial semi-bandits, where input contexts are mapped into subsets of size $m$ of a collection of $K$ possible actions. In each round, the learner observes the realized reward of the predicted…

Machine Learning · Computer Science 2026-02-24 Liad Erez , Tomer Koren

Classification of ordinal data is one of the most important tasks of relation learning. In this thesis a novel framework for ordered classes is proposed. The technique reduces the problem of classifying ordered classes to the standard…

Artificial Intelligence · Computer Science 2007-05-23 Jaime S. Cardoso

We present a semantics for adding uncertainty to conditional logics for default reasoning and belief revision. We are able to treat conditional sentences as statements of conditional probability, and express rules for revision such as "If A…

Artificial Intelligence · Computer Science 2013-03-08 Craig Boutilier

In this paper we propose a method to obtain global explanations for trained black-box classifiers by sampling their decision function to learn alternative interpretable models. The envisaged approach provides a unified solution to…

Machine Learning · Computer Science 2018-11-26 Irene Unceta , Jordi Nin , Oriol Pujol

Option-critic learning is a general-purpose reinforcement learning (RL) framework that aims to address the issue of long term credit assignment by leveraging temporal abstractions. However, when dealing with extended timescales, discounting…

Machine Learning · Computer Science 2019-11-21 Akshay Dharmavaram , Matthew Riemer , Shalabh Bhatnagar

The forcing theorem is the most fundamental result about set forcing, stating that the forcing relation for any set forcing is definable and that the truth lemma holds, that is everything that holds in a generic extension is forced by a…

Logic · Mathematics 2017-10-31 Peter Holy , Regula Krapf , Philipp Lücke , Ana Njegomir , Philipp Schlicht

We study a class of determinantal ideals that are related to conditional independence (CI) statements with hidden variables. Such CI statements correspond to determinantal conditions on a matrix whose entries are probabilities of events…

Commutative Algebra · Mathematics 2023-01-02 Oliver Clarke , Fatemeh Mohammadi , Johannes Rauh

A causal structure is a description of the functional dependencies between random variables. A distribution is compatible with a given causal structure if it can be realized by a process respecting these dependencies. Deciding whether a…

Quantum Physics · Physics 2024-03-25 Laurens T. Ligthart , Mariami Gachechiladze , David Gross

Selective classification is a powerful tool for automated decision-making in high-risk scenarios, allowing classifiers to act only when confident and abstain when uncertainty is high. Given a target accuracy, our goal is to minimize…

Statistics Theory · Mathematics 2025-10-28 Mohamed Ndaoud , Peter Radchenko , Bradley Rava

We characterize incentive compatible mechanisms in environments with hidden types and flexible hidden actions. Our approach introduces extended recommendation schedules that specify prescribed actions also off-path, after misreports. This…

Theoretical Economics · Economics 2025-09-16 Henrique Castro-Pires , Deniz Kattwinkel , Jan Knoepfle

The $\lambda$-superposition calculus is a successful approach to proving higher-order formulas. However, some parts of the calculus are extremely explosive, notably due to the higher-order unifier enumeration and the functional…

Logic in Computer Science · Computer Science 2025-10-22 Alexander Bentkamp , Jasmin Blanchette , Matthias Hetzenberger , Uwe Waldmann

In many modern regression applications, the response consists of multiple categorical random variables whose probability mass is a function of a common set of predictors. In this article, we propose a new method for modeling such a…

Methodology · Statistics 2024-05-15 Aaron J. Molstad , Xin Zhang

We study the problem of stochastic contextual bandits in the agnostic setting, where the goal is to compete with the best policy in a given class without assuming realizability or imposing model restrictions on losses or rewards. In this…

Machine Learning · Statistics 2026-04-06 Samuel Girard , Aurelien Bibaut , Arthur Gretton , Nathan Kallus , Houssam Zenati

A semantics is given to possibilistic logic, a logic that handles weighted classical logic formulae, and where weights are interpreted as lower bounds on degrees of certainty or possibility, in the sense of Zadeh's possibility theory. The…

Artificial Intelligence · Computer Science 2013-03-26 Jerome Lang , Didier Dubois , Henri Prade

Formal models of learning from teachers need to respect certain criteria to avoid collusion. The most commonly accepted notion of collusion-freeness was proposed by Goldman and Mathias (1996), and various teaching models obeying their…

Machine Learning · Computer Science 2019-03-12 David Kirkpatrick , Hans U. Simon , Sandra Zilles

We introduce and study a natural class of fields in which certain first-order definable sets are existentially definable, and characterise this class by a number of equivalent conditions. We show that global fields belong to this class, and…

Logic · Mathematics 2023-06-22 Philip Dittmann , Dion Leijnse

We propose terminology to classify interpretations of quantum mechanics and models that modify or complete quantum mechanics. Our focus is on models which have previously been referred to as superdeterministic (strong or weak), retrocausal…

Quantum Physics · Physics 2024-07-16 Emily Adlam , Jonte R. Hance , Sabine Hossenfelder , Tim N. Palmer