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In this paper, we discuss a potential agenda for future work in the theory of random sets and belief functions, touching upon a number of focal issues: the development of a fully-fledged theory of statistical reasoning with random sets,…

Statistics Theory · Mathematics 2024-01-19 Fabio Cuzzolin

Nowadays we are witnessing a transformation of the business processes towards a more computation driven approach. The ever increasing usage of Machine Learning techniques is the clearest example of such trend. This sort of revolution is…

Machine Learning · Computer Science 2022-03-18 Giorgio Visani , Enrico Bagli , Federico Chesani , Alessandro Poluzzi , Davide Capuzzo

The existence of a positive and possibly varying Lambda-term opens a much wider field of possibilities for the future of our Universe than it was usually thought before. Definite predictions may be made for finite (though very large)…

Astrophysics · Physics 2008-11-26 A. A. Starobinsky

Recidivism prediction instruments provide decision makers with an assessment of the likelihood that a criminal defendant will reoffend at a future point in time. While such instruments are gaining increasing popularity across the country,…

Applications · Statistics 2016-10-25 Alexandra Chouldechova

In this study an attempt has been made to propose a way to develop new distribution. For this purpose, we need only idea about distribution function. Some important statistical properties of the new distribution like moments, cumulants,…

Methodology · Statistics 2024-08-30 Brijesh P. Singh , Utpal Dhar Das

As the Universe expands, the redshift of distant sources changes with time. Here we discuss gravitational lensing phenomena that are consequence of the redshift drift between lensed source, gravitational lens, and observer. When the source…

Cosmology and Nongalactic Astrophysics · Physics 2022-06-01 Giovanni Covone , Mauro Sereno

Optimization is widely used in statistics, and often efficiently delivers point estimates on useful spaces involving structural constraints or combinatorial structure. To quantify uncertainty, Gibbs posterior exponentiates the negative loss…

Methodology · Statistics 2025-07-23 Cheng Zeng , Eleni Dilma , Jason Xu , Leo L Duan

Trading strategies that were profitable in the past often degrade with time. Since unlucky streaks can also hit "healthy" strategies, how can one detect that something truly worrying is happening? It is intuitive that a drawdown that lasts…

Portfolio Management · Quantitative Finance 2017-07-24 Adam Rej , Philip Seager , Jean-Philippe Bouchaud

Selective inference is the problem of giving valid answers to statistical questions chosen in a data-driven manner. A standard solution to selective inference is simultaneous inference, which delivers valid answers to the set of all…

Methodology · Statistics 2024-05-03 Tijana Zrnic , William Fithian

Discussions on indeterminism in physics focus on the possibility of an open future, i.e. the possibility of having potential alternative future events, the realisation of one of which is not fully determined by the present state of affairs.…

History and Philosophy of Physics · Physics 2023-02-21 Flavio Del Santo , Nicolas Gisin

We consider several variants of a class of random walks whose increment distributions depend on the average value of the process over its most recent $N$ steps. We investigate the speed of the process, and in particular, the limiting speed…

Probability · Mathematics 2019-03-29 Ross G. Pinsky

For the last ten years, almost every theoretical result concerning the expected run time of a randomized search heuristic used drift theory, making it the arguably most important tool in this domain. Its success is due to its ease of use…

Probability · Mathematics 2018-05-25 Timo Kötzing , Martin S. Krejca

We consider an ergodic process on finitely many states, with positive entropy. Our first main result asserts that the distribution function of the normalized waiting time for the first visit to a small (i.e., over a long block) cylinder set…

Probability · Mathematics 2008-10-27 Tomasz Downarowicz , Yves Lacroix

The call for patient-focused drug development is loud and clear, as expressed in the 21st Century Cures Act and in recent guidelines and initiatives of regulatory agencies. Among the factors contributing to modernized drug development and…

The Manifold Hypothesis is a widely accepted tenet of Machine Learning which asserts that nominally high-dimensional data are in fact concentrated near a low-dimensional manifold, embedded in high-dimensional space. This phenomenon is…

Methodology · Statistics 2025-03-24 Nick Whiteley , Annie Gray , Patrick Rubin-Delanchy

Real-world deployment of machine learning models is challenging because data evolves over time. While no model can work when data evolves in an arbitrary fashion, if there is some pattern to these changes, we might be able to design methods…

Machine Learning · Computer Science 2024-05-03 Rasool Fakoor , Jonas Mueller , Zachary C. Lipton , Pratik Chaudhari , Alexander J. Smola

Traditional clustering identifies groups of objects that share certain qualities. Tangles do the converse: they identify groups of qualities that often occur together. They can thereby identify and discover 'types': of behaviour, views,…

Combinatorics · Mathematics 2019-07-18 Reinhard Diestel

The Matthew effect refers to the adage written some two-thousand years ago in the Gospel of St. Matthew: "For to all those who have, more will be given." Even two millennia later, this idiom is used by sociologists to qualitatively describe…

Popular Physics · Physics 2011-03-17 Alexander M. Petersen , Woo-Sung Jung , Jae-Suk Yang , H. Eugene Stanley

The fluctuation relations, which characterize irreversible processes in Nature, are among the most important results in non-equilibrium physics. In short, these relations say that it is exponentially unlikely for us to observe a…

Quantum Physics · Physics 2023-08-30 Marcos L. W. Basso , Jonas Maziero , Lucas C. Céleri

The sudden appearance of modern machine learning (ML) phenomena like double descent and benign overfitting may leave many classically trained statisticians feeling uneasy -- these phenomena appear to go against the very core of statistical…

Machine Learning · Statistics 2024-09-30 Alicia Curth