Hitting time of large subsets of the hypercube

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Many applications, e.g. in content recommendation, sports, or recruitment, leverage the comparisons of alternatives to score those alternatives. The classical Bradley-Terry model and its variants have been widely used to do so. The historical model conside ...

Modern digital connectivity has necessitated the creation of robust methods for securely storing and transferring data. At the heart of all security infrastructure is the random number generator (RNG). While random numbers find use in a variety of applicat ...

Electric vehicle charging facilities offer their capacity constrained electric charge and parking to users for a fee. As electric vehicle adoption grows, so too does the potential for excessive resource utilization. In this paper, we study how prices set b ...

This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...

In this work, we tackle the problem of minimising the Conditional-Value-at-Risk (CVaR) of output quantities of complex differential models with random input data, using gradient-based approaches in combination with the Multi-Level Monte Carlo (MLMC) method ...

The discretization of robust quadratic optimal control problems under uncertainty using the finite element method and the stochastic collocation method leads to large saddle-point systems, which are fully coupled across the random realizations. Despite its ...

We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an identically distribute ...

We consider one-dimensional excited random walks (ERWs) with i.i.d. Markovian cookie stacks in the non-boundary recurrent regime. We prove that under diffusive scaling such an ERW converges in the standard Skorokhod topology to a multiple of Brownian motio ...

True random number generators (TRNGs) allow the generation of true random bit sequences, guaranteeing the unpredictability and perfect balancing of the generated values. TRNGs can be realised from the sampling of quantum phenomena, for instance, the detect ...

We introduce the "continuized" Nesterov acceleration, a close variant of Nesterov acceleration whose variables are indexed by a continuous time parameter. The two variables continuously mix following a linear ordinary differential equation and take gradien ...

An animals' ability to learn how to make decisions based on sensory evidence is often well described by Reinforcement Learning (RL) frameworks. These frameworks, however, typically apply to event-based representations and lack the explicit and fine-grained ...

Given a sequence L & x2d9;epsilon of Levy noises, we derive necessary and sufficient conditions in terms of their variances sigma 2(epsilon) such that the solution to the stochastic heat equation with noise sigma(epsilon)-1L & x2d9;epsilon converges in law ...

We establish probabilistic small data global well-posedness of the energy-critical Maxwell-Klein-Gordon equation relative to the Coulomb gauge for scaling super-critical random initial data. The proof relies on an induction on frequency procedure and a mod ...

This paper introduces a new algorithm for consensus optimization in a multi-agent network, where all agents collaboratively find a minimizer for the sum of their private functions. All decentralized algorithms rely on communications between adjacent nodes. ...

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max-stable models are inadequate to capture the rate of joint tail decay, and to estimate jo ...

This work presents a technique to produce random bits by exploiting single-photon time of arrival. Two quantum random number generator (QRNG) devices based on the field programmable gate array (FPGA) technology are presented: Randy, which uses one discrete ...

Many techniques for data science and uncertainty quantification demand efficient tools to handle Gaussian random fields, which are defined in terms of their mean functions and covariance operators. Recently, parameterized Gaussian random fields have gained ...

Making decisions is part and parcel of being human. Among a set of actions, we want to choose the one that has the highest reward. But the uncertainty of the outcome prevents us from always making the right decision. Making decisions under uncertainty can ...

Consider a random process s that is a solution of the stochastic differential equation Ls = w with L a homogeneous operator and w a multidimensional Levy white noise. In this paper, we study the asymptotic effect of zooming in or zooming out of the process ...

Max-stable random fields are very appropriate for the statistical modelling of spatial extremes. Hence, integrals of functions of max-stable random fields over a given region can play a key role in the assessment of the risk of natural disasters, meaning t ...

Hitting time of large subsets of the hypercube

Chattez avec Graph Search

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Modelling and design of CMOS SPAD sensors for quantum random number generation

Resource aware pricing for electric vehicle charging

Optimal Matching of Random Parts

Gradient-based optimisation of the conditional-value-at-risk using the multi-level Monte Carlo method

Preconditioners for robust optimal control problems under uncertainty

Functional estimation of anisotropic covariance and autocovariance operators on the sphere

Convergence of random walks with Markovian cookie stacks to Brownian motion perturbed at extrema

Certification of the efficient random number generation technique based on single-photon detector arrays and time-to-digital converters

A Continuized View on Nesterov Acceleration

Learning continuous-time working memory tasks with on-policy neural reinforcement learning

Normal approximation of the solution to the stochastic heat equation with Levy noise

Probabilistic small data global Well-Posedness of the energy-critical Maxwell-Klein-Gordon equation

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

Max-infinitely divisible models and inference for spatial extremes

Efficient random number generation techniques for CMOS single-photon avalanche diode array exploiting fast time tagging units

Certified And Fast Computations With Shallow Covariance Kernels

Multi-armed Bandits in Action

Scaling Limits of Solutions of Linear Stochastic Differential Equations Driven by Levy White Noises

A central limit theorem for functions of stationary max-stable random fields on R-d