Publications associées à Méthode delta

Sub‐asymptotic motivation for new conditional multivariate extreme models

Anthony Christopher Davison, Thomas Lugrin, Jonathan A. Tawn

Statistical models for extreme values are generally derived from non-degenerate probabilistic limits that can be used to approximate the distribution of events that exceed a selected high threshold. If convergence to the limit distribution is slow, then th ...

2021

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Daniel Kuhn, Viet Anh Nguyen, Bahar Taskesen

Least squares estimators, when trained on a few target domain samples, may predict poorly. Supervised domain adaptation aims to improve the predictive accuracy by exploiting additional labeled training samples from a source distribution that is close to th ...

2021

High-Frequency Analysis Of Parabolic Stochastic Pdes

Carsten Hao Ye Chong

We consider the problem of estimating stochastic volatility for a class of second-order parabolic stochastic PDEs. Assuming that the solution is observed at high temporal frequency, we use limit theorems for multipower variations and related functionals to ...

INST MATHEMATICAL STATISTICS2020

Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations

Michel Bierlaire, Prateek Bansal

Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to Markov chain Monte Carlo (MCMC) methods for scalable Bayesian estimation of mixed multinomial logit (MMNL) models. It has been established that VB is substan ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Support and approximation properties of Hermite splines

Michaël Unser, Julien René Pierre Fageot, Virginie Sophie Uhlmann, Shayan Aziznejad

In this paper, we formally investigate two mathematical aspects of Hermite splines that are relevant to practical applications. We first demonstrate that Hermite splines are maximally localized, in the sense that the size of their support is minimal among ...

2020

MATHICSE Technical Report: Accelerated convergence to equilibrium and reduced asymptotic variance for Langevin dynamics using Stratonovich perturbations

Assyr Abdulle, Gilles Vilmart, Grigorios A. Pavliotis

In this paper we propose a new approach for sampling from probability measures in, possibly, high dimensional spaces. By perturbing the standard overdamped Langevin dynamics by a suitable Stratonovich perturbation that preserves the invariant measure of th ...

MATHICSE2019

Accelerated convergence to equilibrium and reduced asymptotic variance for Langevin dynamics using Stratonovich perturbations

Assyr Abdulle, Gilles Vilmart, Grigorios A. Pavliotis

In this paper, we propose a new approach for sampling from probability measures in, possibly, high-dimensional spaces. By perturbing the standard overdamped Langevin dynamics by a suitable Stratonovich perturbation that preserves the invariant measure of t ...

2019

Small-variance asymptotics for non-parametric online robot learning

Sylvain Calinon, Ajay Kumar Tanwani

Small-variance asymptotics is emerging as a useful technique for inference in large-scale Bayesian non-parametric mixture models. This paper analyzes the online learning of robot manipulation tasks with Bayesian non-parametric mixture models under small-va ...

SAGE PUBLICATIONS LTD2019

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Méthode delta

Sub‐asymptotic motivation for new conditional multivariate extreme models

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

High-Frequency Analysis Of Parabolic Stochastic Pdes

Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations

Support and approximation properties of Hermite splines

Contributions to Likelihood-Based Modelling of Extreme Values

MATHICSE Technical Report: Accelerated convergence to equilibrium and reduced asymptotic variance for Langevin dynamics using Stratonovich perturbations

Accelerated convergence to equilibrium and reduced asymptotic variance for Langevin dynamics using Stratonovich perturbations

Small-variance asymptotics for non-parametric online robot learning

Small Variance Asymptotics for Non-Parametric Online Robot Learning

Graph Chatbot

Chattez avec Graph Search

Accelerated convergence to equilibrium and reduced asymptotic variance for Langevin dynamics using Stratonovich perturbations

Contributions to Likelihood-Based Modelling of Extreme Values

High-Frequency Analysis Of Parabolic Stochastic Pdes

Sub‐asymptotic motivation for new conditional multivariate extreme models

Small Variance Asymptotics for Non-Parametric Online Robot Learning

Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations

Support and approximation properties of Hermite splines

MATHICSE Technical Report: Accelerated convergence to equilibrium and reduced asymptotic variance for Langevin dynamics using Stratonovich perturbations

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Small-variance asymptotics for non-parametric online robot learning