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Related papers: Exchangeable choice functions

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We present a novel model architecture which leverages deep learning tools to perform exact Bayesian inference on sets of high dimensional, complex observations. Our model is provably exchangeable, meaning that the joint distribution over…

Machine Learning · Statistics 2018-10-17 Iryna Korshunova , Jonas Degrave , Ferenc Huszár , Yarin Gal , Arthur Gretton , Joni Dambre

We define an equivalence relation on propositions and a proof system where equivalent propositions have the same proofs. The system obtained this way resembles several known non-deterministic and algebraic lambda-calculi.

Logic in Computer Science · Computer Science 2013-04-01 Alejandro Díaz-Caro , Gilles Dowek

Conformal prediction is a powerful framework for distribution-free uncertainty quantification. The standard approach to conformal prediction relies on comparing the ranks of prediction scores: under exchangeability, the rank of a future…

Machine Learning · Statistics 2025-05-07 Etienne Gauthier , Francis Bach , Michael I. Jordan

Choice revision is a sort of non-prioritized multiple revision, in which the agent partially accepts the new information represented by a set of sentences. We investigate the construction of choice revision based on a new approach to belief…

Logic · Mathematics 2018-05-02 Li Zhang

In this paper, we investigate the structure of the most general kind of substitution shifts, including non-minimal ones, and allowing erasing morphisms. We prove the decidability of many properties of these morphisms with respect to the…

Dynamical Systems · Mathematics 2024-04-03 Marie-Pierre Béal , Dominique Perrin , Antonio Restivo

We study functional and concurrent calculi with non-determinism, along with type systems to control resources based on linearity. The interplay between non-determinism and linearity is delicate: careless handling of branches can discard…

Logic in Computer Science · Computer Science 2023-10-02 Bas van den Heuvel , Joseph W. N. Paulus , Daniele Nantes-Sobrinho , Jorge A. Pérez

Decision trees are widely used for interpretable machine learning due to their clearly structured reasoning process. However, this structure belies a challenge we refer to as predictive equivalence: a given tree's decision boundary can be…

Machine Learning · Computer Science 2025-10-15 Hayden McTavish , Zachery Boner , Jon Donnelly , Margo Seltzer , Cynthia Rudin

The paper studies complementary choice functions, i.e. monotonic and consistent choice functions. Such choice functions were introduced and used in the work \cite{RY} for investigation of matchings with complementary contracts. Three…

Combinatorics · Mathematics 2022-09-15 Vladimir Danilov

We consider trading indivisible and easily transferable \emph{durable goods}, which are goods that an agent can receive, use, and trade again for a different good. This is often the case with books that can be read and later exchanged for…

Computer Science and Game Theory · Computer Science 2021-10-28 Sigal Oren , Oren Roth

This chapter explores the role of substitutability in economic models, particularly in the context of optimal transport and matching models. In equilibrium models with substitutability, market-clearing prices can often be recovered using…

Theoretical Economics · Economics 2024-05-14 Alfred Galichon , Antoine Jacquet

We argue for the use of separate exchangeability as a modeling principle in Bayesian nonparametric (BNP) inference. Separate exchangeability is de facto widely applied in the Bayesian parametric case, e.g., it naturally arises in simple…

Methodology · Statistics 2025-07-29 Giovanni Rebaudo , Qiaohui Lin , Peter Mueller

The lack of interpretability and transparency are preventing economists from using advanced tools like neural networks in their empirical research. In this paper, we propose a class of interpretable neural network models that can achieve…

Econometrics · Economics 2020-12-01 Yucheng Yang , Zhong Zheng , Weinan E

We present a class of one-to-one matching models with perfectly transferable utility. We discuss identification and inference in these separable models, and we show how their comparative statics are readily analyzed.

Econometrics · Economics 2021-02-05 Alfred Galichon , Bernard Salanié

Inferential models (IMs) are data-dependent, imprecise-probabilistic structures designed to quantify uncertainty about unknowns. As the name suggests, the focus has been on uncertainty quantification for inference and on its reliability…

Statistics Theory · Mathematics 2026-05-01 Ryan Martin , Shih-Ni Prim , Jonathan Williams

An approach to induction is presented, based on the idea of analysing the context of a given problem into `circumstances'. This approach, fully Bayesian in form and meaning, provides a complement or in some cases an alternative to that…

Data Analysis, Statistics and Probability · Physics 2007-05-23 P. G. L. Porta Mana , A. Månsson , G. Björk

We provide sufficient conditions under which a utility function may be recovered from a finite choice experiment. Identification, as is commonly understood in decision theory, is not enough. We provide a general recoverability result that…

Theoretical Economics · Economics 2023-01-30 Christopher P. Chambers , Federico Echenique , Nicolas S. Lambert

A combinatorial characterization of measurable filters on a countable set is found. We apply it to the problem of measurability of the intersection of nonmeasurable filters.

Logic · Mathematics 2007-05-23 Tomek Bartoszynski

Given information about which options a decision-maker definitely rejects from given finite sets of options, we study the implications for decision-making with E-admissibility. This means that from any finite set of options, we reject those…

Artificial Intelligence · Computer Science 2022-05-13 Arne Decadt , Alexander Erreygers , Jasper De Bock , Gert de Cooman

Let A be a standard Borel space, and consider the space A^{\bbN^{(k)}} of A-valued arrays indexed by all size-k subsets of \bbN. This paper concerns random measures on such a space whose laws are invariant under the natural action of…

Probability · Mathematics 2015-07-09 Tim Austin

We study the independence structure of finitely exchangeable distributions over random vectors and random networks. In particular, we provide necessary and sufficient conditions for an exchangeable vector so that its elements are completely…

Statistics Theory · Mathematics 2020-06-15 Kayvan Sadeghi
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