Concept

Canonical correlation

Related publications (52)

INTRA-CLASS COVARIANCE ADAPTATION IN PLDA BACK-ENDS FOR SPEAKER VERIFICATION

Multi-session training conditions are becoming increasingly common in recent benchmark datasets for both text-independent and text-dependent speaker verification. In the state-of-the-art i-vector framework for speaker verification, such conditions are addr ...

Ieee2017

Caching Gaussians: Minimizing Total Correlation on the Gray–Wyner Network

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

We study a caching problem that resembles a lossy Gray–Wyner network: A source produces vector samples from a Gaussian distribution, but the user is interested in the samples of only one component. The encoder first sends a cache message without any knowle ...

Ieee2016

Statistical structure of neural spiking under non-Poissonian or other non-white stimulation

Tilo Schwalger

Nerve cells in the brain generate sequences of action potentials with a complex statistics. Theoretical attempts to understand this statistics were largely limited to the case of a temporally uncorrelated input (Poissonian shot noise) from the neurons in t ...

Springer2015

Femtosecond resolution timing jitter correction on a TW scale Ti:sapphire laser system for FEL pump-probe experiments

Christoph Peter Hauri

Intense ultrashort pulse lasers are used for fs resolution pumpprobe experiments more and more at large scale facilities, such as free electron lasers (FEL). Measurement of the arrival time of the laser pulses and stabilization to the machine or other sub- ...

Optical Society of America2015

Scalable Probabilistic Models for Face and Speaker Recognition

Laurent El Shafey

In the biometrics community, face and speaker recognition are mature fields in which several systems have been proposed over the past twenty years. While existing systems perform well under controlled recording conditions, mismatch caused by the use of dif ...

EPFL2014

Principal Flows

Victor Panaretos, Tung Huy Pham, Zhigang Yao

We revisit the problem of extending the notion of principal component analysis (PCA) to multivariate datasets that satisfy nonlinear constraints, therefore lying on Riemannian manifolds. Our aim is to determine curves on the manifold that retain their cano ...

American Statistical Association2014

Notes on Probabilistic Linear Discriminant Analysis

Laurent El Shafey

The following are a set of working notes on how to derive and implement probabilistic linear discriminant analysis (PLDA) using Gaussian priors. ...

Idiap2013

Investigating Reliability on Fuel Cell Model Identification. Part III: Behavior of Assessment Criteria and Limits in Identification

Daniel Favrat, Jan Van Herle, Leonidas Tsikonis

The present paper is the third and last part of an investigation on what determines reliability in fuel cell model identification. In continuation to the effect of experimental design (Part I) and a process method for stochastic calculation of a model's pa ...

Wiley-V C H Verlag Gmbh2013

A Scalable Formulation of Probabilistic Linear Discriminant Analysis: Applied to Face Recognition

Sébastien Marcel, Laurent El Shafey

In this paper we present a scalable and exact solution for probabilistic linear discriminant analysis (PLDA). PLDA is a probabilistic model that has been shown to provide state-of-the-art performance for both face and speaker recognition. However, it has o ...

Ieee Computer Soc2013

A Scalable Formulation of Probabilistic Linear Discriminant Analysis: Applied to Face Recognition

Sébastien Marcel, Laurent El Shafey

Idiap2013

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