Publications related to Extremal behavior of squared Bessel processes attracted by the Brown-Resnick process

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

Fabio Nobile, Giovanni Migliorati, Erik Gustaf Bogislaw Von Schwerin

In this work we consider the random discrete

L^2

projection on polynomial spaces (hereafter RDP) for the approximation of scalar quantities of interest (QOIs) related to the solution of a partial differential equation model with random input parameters. ...

Siam Publications2013

Optimal Classification In Sparse Gaussian Graphic Model

Zhigang Yao, Yingying Fan

Consider a two-class classification problem where the number of features is much larger than the sample size. The features are masked by Gaussian noise with mean zero and covariance matrix Sigma, where the precision matrix Omega = Sigma(-1) is unknown but ...

Institute of Mathematical Statistics2013

Learning Ridge Functions With Randomized Sampling In High Dimensions

Volkan Cevher, Hemant Tyagi

We study the problem of learning ridge functions of the form f(x) = g(aT x), x ∈ ℝd, from random samples. Assuming g to be a twice continuously differentiable function, we leverage techniques from low rank matrix recovery literature to derive a uniform app ...

IEEE2012

Visual spatiotemporal processing in the elderly

Michael Herzog

We used backward masking paradigm to investigate the effects of aging on visual spatiotemporal processing. First, thirty-three older (M=65.3 years) and ten younger adults (M=24.3 years) had to indicate the offset direction of a vernier that was masked by a ...

Pion Ltd.2012

Maximum-Likelihood Identification of Sampled Gaussian Processes

Michaël Unser, Hagay Kirshner, Simona Maggio

This work considers sampled data of continuous-domain Gaussian processes. We derive a maximum-likelihood estimator for identifying autoregressive moving average parameters while incorporating the sampling process into the problem formulation. The proposed ...

SampTA2011

Anthropic Correction of Information Estimates

Michael Christoph Gastpar

A novel estimator for mutual information is proposed. The estimator is useful for the (asymmetric) scenario where only a few samples for one random variable are available, but for each sample, the conditional distribution of the other random variable can b ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Reduced basis method for multi-parameter dependent steady Navier-Stokes equations: applications to natural convection in a cavity

Simone Deparis, Gianluigi Rozza

This work focuses on the approximation of parametric steady Navier-- Stokes equations by the reduced basis method. For a particular instance of the parameters under consideration, we are able to solve the underlying partial differential equations, compute ...

2009

Multi-experts scheduling system for real-time applications

Mario Bellino

This thesis focuses on the decisional process of autonomous systems, and more particularly, on the way to take a decision when the time at disposal in order to assess the whole situation is shorter than necessary. Indeed, numerous systems propose solutions ...

EPFL2009

Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures

We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multi- scale image representation. Neighborhoods are modeled as samples of a multivariate Gaussian density that are modulated and rotated ...

2008

Invariances in Kernel Methods: From Samples to Objects

Samy Bengio, Alexei Pozdnoukhov

This paper presents a general method for incorporating prior knowledge into kernel methods such as Support Vector Machines. It applies when the prior knowledge can be formalized by the description of an object around each sample of the training set, assumi ...

IDIAP2004

Extremal behavior of squared Bessel processes attracted by the Brown-Resnick process

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Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

Optimal Classification In Sparse Gaussian Graphic Model

Learning Ridge Functions With Randomized Sampling In High Dimensions

Visual spatiotemporal processing in the elderly

Maximum-Likelihood Identification of Sampled Gaussian Processes

Anthropic Correction of Information Estimates

Reduced basis method for multi-parameter dependent steady Navier-Stokes equations: applications to natural convection in a cavity

Multi-experts scheduling system for real-time applications

Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures

Invariances in Kernel Methods: From Samples to Objects

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

Optimal Classification In Sparse Gaussian Graphic Model

Learning Ridge Functions With Randomized Sampling In High Dimensions

Visual spatiotemporal processing in the elderly

Anthropic Correction of Information Estimates

Multi-experts scheduling system for real-time applications

Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures

Maximum-Likelihood Identification of Sampled Gaussian Processes

Reduced basis method for multi-parameter dependent steady Navier-Stokes equations: applications to natural convection in a cavity

Invariances in Kernel Methods: From Samples to Objects