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Correcting Jackknife Confidence Intervals

Publications associées (107)

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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

Fast initialization of particle filters using a modified Metropolis-Hastings algorithm: Mode-hungry approach

Volkan Cevher

As a recursive algorithm, the particle filter requires initial samples to track a state vector. These initial samples must be generated from the received data and usually obey a complicated distribution. The Metropolis-Hastings (M-H) algorithm is used for ...

2004

Evaluation and visualization of stress and strain on soft biological tissues in contact

Daniel Thalmann, Ronan Boulic, Sofiane Sarni, Anderson Maciel

This paper addresses evaluation and visualization of stress and strain on soft biological tissues in contact given three-dimensional models of reconstructed organs from magnetic resonance images (MRI), we use an anatomy-based kinematical model combined wit ...

IEEE2004

Enhanced Performance of Multimodal Biometric Systems by Confidence Estimation

The main scope of this project is to identify the best method of confidence estimator whose performance could be reliable in comparison to multimodal fusion alone. To do that, three alternative approaches to prediction confidence estimation are presented a ...

IDIAP2003

Non-Kolmogorov-Avrami switching kinetics in ferroelectric thin films

Nava Setter, Alexander Tagantsev, Igor Stolichnov

The switching kinetics in ferroelectric thin films has been intensively studied during the past decade. It is widely accepted that this kinetics is basically governed by the dynamics of domain coalescence (the Kolmogorov-Avrami-Ishibashi model). This concl ...

2002

Computer-intensive statistical methods

Diego Kuonen

The saddlepoint approximation was introduced into statistics in 1954 by Henry E. Daniels. This basic result on approximating the density function of the sample mean has been generalized to many situations. The accuracy of this approximation is very good, p ...

EPFL2001

Confidence Evaluation for Risk Prediction

This paper describe an application of a transductive method for risk mapping which allows to compute the confidence interval of an estimation, without any assumption on data distribution, except identity and independancy of inputs. The method is compared t ...

2001

Confidence Evaluation for Risk Prediction

IDIAP2001

A method for polarisation imaging using digital holography

Christian Depeursinge, Tristan Colomb, Etienne Cuche

A numerical holographic method, which is able to determine the amplitude components of the Jones vector of a wavefront in addition to its phase and amplitude, is presented. Two reference waves, with orthogonal polarisations interfere with the transmitted o ...

Springer-Verlag Berlin2000

Estimating Distribution Functions with Smoothing Splines

Eva Maria Restle

The scope is to smooth the empirical distribution function of a random sample by minimizing a penalized sum of squared errors. The spline, which is the solution to this problem, is studied via the eigenvalue structure of the random matrices ocurring in its ...

1999