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Energy-based learning is a powerful framework for generative modelling, but its training is inherently non-convex, leading potentially to sensitivity to initialisation, poor local optima, and unstable gradient dynamics. We present a…

Machine Learning · Computer Science 2026-05-11 Aurélien Decelle , Alfonso de Jesús Navas Gómez , Beatriz Seoane

We study a general class of bilevel problems, consisting in the minimization of an upper-level objective which depends on the solution to a parametric fixed-point equation. Important instances arising in machine learning include…

Machine Learning · Statistics 2020-07-13 Riccardo Grazzi , Luca Franceschi , Massimiliano Pontil , Saverio Salzo

Computing expected predictions of discriminative models is a fundamental task in machine learning that appears in many interesting applications such as fairness, handling missing values, and data analysis. Unfortunately, computing…

Machine Learning · Computer Science 2019-11-04 Pasha Khosravi , YooJung Choi , Yitao Liang , Antonio Vergari , Guy Van den Broeck

We study extremal statistics and return intervals in stationary long-range correlated sequences for which the underlying probability density function is bounded and uniform. The extremal statistics we consider e.g., maximum relative to…

Statistical Mechanics · Physics 2015-05-13 N. R. Moloney , J. Davidsen

The choice of how to represent an abstract type can have a major impact on the performance of a program, yet mainstream compilers cannot perform optimizations at such a high level. When dealing with optimizations of data type…

Programming Languages · Computer Science 2024-09-13 Viktor Palmkvist , Anders Ågren Thuné , Elias Castegren , David Broman

Object queries are essential in information seeking and decision making in vast areas of applications. However, a query may involve complex conditions on objects and sets, which can be arbitrarily nested and aliased. The objects and sets…

Programming Languages · Computer Science 2020-12-25 Yanhong A. Liu , Jon Brandvein , Scott D. Stoller , Bo Lin

Consider the problem of imputing missing values in a dataset. One the one hand, conventional approaches using iterative imputation benefit from the simplicity and customizability of learning conditional distributions directly, but suffer…

Machine Learning · Statistics 2022-06-17 Daniel Jarrett , Bogdan Cebere , Tennison Liu , Alicia Curth , Mihaela van der Schaar

We consider the problem of estimating the sparse time-varying parameter vectors of a point process model in an online fashion, where the observations and inputs respectively consist of binary and continuous time series. We construct a novel…

Neural and Evolutionary Computing · Computer Science 2016-04-20 Alireza Sheikhattar , Jonathan B. Fritz , Shihab A. Shamma , Behtash Babadi

We describe how to apply the transport method to compute inflationary observables in a broad range of multiple-field models. The method is efficient and encompasses scenarios with curved field-space metrics, violations of slow-roll…

Cosmology and Nongalactic Astrophysics · Physics 2016-01-20 Mafalda Dias , Jonathan Frazer , David Seery

Recursive graph queries are increasingly popular for extracting information from interconnected data found in various domains such as social networks, life sciences, and business analytics. Graph data often come with schema information that…

Databases · Computer Science 2025-02-13 Chandan Sharma , Pierre Genevès , Nils Gesbert , Nabil Layaïda

Inflation with a scalar-field potential of the form \lambda (\phi^2-v^2)^2 can be described in terms of a parametrical attractor with critical points, whose driftage depends on the control value of the slowly changing Hubble rate. The…

General Relativity and Quantum Cosmology · Physics 2014-11-20 V. V. Kiselev , S. A. Timofeev

This paper considers a network of infinite-server queues with the special feature that, triggered by specific events, the network population vector may undergo a linear transformation (a `multiplicative transition'). For this model we…

Probability · Mathematics 2017-11-15 Dieter Fiems , Michel Mandjes , Brendan Patch

Monthly and weekly economic indicators are often taken to be the largest common factor estimated from high and low frequency data, either separately or jointly. To incorporate mixed frequency information without directly modeling them, we…

Econometrics · Economics 2023-10-10 Serena Ng , Susannah Scanlan

We provide an economically sound micro-foundation to linear price impact models, by deriving them as the equilibrium of a suitable agent-based system. Our setup generalizes the well-known Kyle model, by dropping the assumption of a terminal…

Trading and Market Microstructure · Quantitative Finance 2021-05-26 Michele Vodret , Iacopo Mastromatteo , Bence Tóth , Michael Benzaquen

In this paper we consider point processes specified on directed linear networks, i.e. linear networks with associated directions. We adapt the so-called conditional intensity function used for specifying point processes on the time line to…

Statistics Theory · Mathematics 2019-01-03 Jakob G. Rasmussen , Heidi S. Christensen

We consider the Quillen adjunction between fixed points and inflation in the context of equivariant module spectra over equivariant ring spectra, and give numerous examples including some based on geometric fixed points and some on the…

Algebraic Topology · Mathematics 2014-10-01 J. P. C. Greenlees , B. Shipley

A novel inflection-point inflation model is analysed. The model considers a massless scalar field, whose self-coupling's running is stabilised by a non-renormalisable operator. The running is controlled by a fermion loop. We find that…

High Energy Physics - Phenomenology · Physics 2018-07-05 Konstantinos Dimopoulos , Charlotte Owen , Antonio Racioppi

We study how a central bank should dynamically set short-term nominal interest rates to stabilize inflation and unemployment when macroeconomic relationships are uncertain and time-varying. We model monetary policy as a sequential…

Statistical Finance · Quantitative Finance 2026-01-06 Tony Wang , Kyle Feinstein , Sheryl Chen

We discuss the existence of inflationary solutions in a class of renormalization group improved polynomial f(R) theories, which have been studied recently in the context of the asymptotic safety scenario for quantum gravity. These theories…

General Relativity and Quantum Cosmology · Physics 2011-07-22 Adriano Contillo

Bayesian clinical trials can benefit of available historical information through the elicitation of informative prior distributions. Concerns are however often raised about the potential for prior-data conflict and the impact of Bayes test…

Methodology · Statistics 2022-12-01 Silvia Calderazzo , Annette Kopp-Schneider