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Rare events are events that are expected to occur infrequently, or more technically, those that have low probabilities (say, order of $10^{-3}$ or less) of occurring according to a probability model. In the context of uncertainty…

Computation · Statistics 2015-08-21 James L. Beck , Konstantin M. Zuev

Predicting the evolution of a large system of units using its structure of interaction is a fundamental problem in complex system theory. And so is the problem of reconstructing the structure of interaction from temporal observations. Here,…

Statistical Mechanics · Physics 2025-02-10 Charles Murphy , Vincent Thibeault , Antoine Allard , Patrick Desrosiers

Serendipity has been associated with numerous benefits in the context of recommender systems, e.g., increased user satisfaction and consumption of long-tail items. Despite this, serendipity in the context of recommender systems has thus far…

Human-Computer Interaction · Computer Science 2025-05-26 Brett Binst , Lien Michiels , Annelien Smets

We introduce a robust belief-based measure of complexity. The idea is that task A is deemed more complex than task B if the probability of solving A correctly is smaller than the probability of solving B correctly regardless of the reward.…

Theoretical Economics · Economics 2025-01-17 Egor Bronnikov , Elias Tsakas

A general notion of information-related complexity applicable to both natural and man-made systems is proposed. The overall approach is to explicitly consider a rational agent performing a certain task with a quantifiable degree of success.…

Data Analysis, Statistics and Probability · Physics 2013-01-18 Eugene Perevalov , David Grace

Event structures where the causality may explicitly change during a computation have recently gained the stage. In this kind of event structures the changes in the set of the causes of an event are triggered by modifiers that may add or…

Logic in Computer Science · Computer Science 2023-06-22 G. Michele Pinna

Humans are sensitive to suspicious coincidences when generalizing inductively over data, as they make assumptions as to how the data was sampled. This results in smaller, more specific hypotheses being favored over more general ones. For…

Computation and Language · Computer Science 2025-04-15 Sriram Padmanabhan , Kanishka Misra , Kyle Mahowald , Eunsol Choi

Ambiguity-averse decision makers typically dislike not only the presence of ambiguous events but also their increase, contrary to what standard ambiguity models predict. We axiomatically study such a decision maker. She avoids ex ante…

Theoretical Economics · Economics 2026-05-25 Yutaro Akita , Kensei Nakamura

The evaluation of the probability of union of a large number of independent events requires several combinations involving the factorial and the use of high performance computers with several hours of processing. Bounds and simplifications…

Numerical Analysis · Mathematics 2025-03-07 Edson Luiz Ursini , Paulo S. Martins

Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity…

Adaptation and Self-Organizing Systems · Physics 2015-02-06 Jonathan Lawhead

Modelling emotion has become a challenge nowadays. Therefore, several models have been produced in order to express human emotional activity. However, only a few of them are currently able to express the close relationship existing between…

Artificial Intelligence · Computer Science 2009-11-13 Karim Mahboub , Evelyne Clément , Cyrille Bertelle , Véronique Jay

Bayesian probability theory is one of the most successful frameworks to model reasoning under uncertainty. Its defining property is the interpretation of probabilities as degrees of belief in propositions about the state of the world…

Artificial Intelligence · Computer Science 2015-04-27 Pedro A. Ortega

We show that it is possible to understand and identify a decision maker's subjective causal judgements by observing her preferences over interventions. Following Pearl [2000], we represent causality using causal models (also called…

Theoretical Economics · Economics 2024-01-23 Joseph Y. Halpern , Evan Piermont

In this paper we look at popular fairness methods that use causal counterfactuals. These methods capture the intuitive notion that a prediction is fair if it coincides with the prediction that would have been made if someone's race, gender…

Machine Learning · Statistics 2022-12-12 Jake Fawkes , Robin Evans , Dino Sejdinovic

This essay is a two-step reflection on the question 'Which events (can be said to) occur in quantum phenomena?' The first step regiments the ontological category of "statistical phenomena" and studies the adequacy of "probabilistic event…

History and Philosophy of Physics · Physics 2025-02-14 Sebastian Horvat

Social networks enable users to freely communicate with each other and share their recent news, ongoing activities or views about different topics. As a result, they can be seen as a potentially viable source of information to understand…

Information Retrieval · Computer Science 2016-06-29 Fattane Zarrinkalam , Ebrahim Bagheri

We consider basic conceptual questions concerning the relationship between statistical estimation and causal inference. Firstly, we show how to translate causal inference problems into an abstract statistical formalism without requiring any…

Statistics Theory · Mathematics 2020-07-22 Oliver J. Maclaren , Ruanui Nicholson

We view sorites in terms of stimuli acting upon a system and evoking this system's responses. Supervenience of responses on stimuli implies that they either lack tolerance (i.e., they change in every vicinity of some of the stimuli), or…

Artificial Intelligence · Computer Science 2015-04-27 Damir D. Dzhafarov , Ehtibar N. Dzhafarov

Understanding the 3D world from 2D images involves more than detection and segmentation of the objects within the scene. It also includes the interpretation of the structure and arrangement of the scene elements. Such understanding is often…

Computer Vision and Pattern Recognition · Computer Science 2022-12-07 Or Nachmias , Ohad Fried , Ariel Shamir

Nonprobability (convenience) samples are increasingly sought to reduce the estimation variance for one or more population variables of interest that are estimated using a randomized survey (reference) sample by increasing the effective…

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