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Distributionally Robust Optimization with Polynomial Densities: Theory, Models and Algorithms

Publications associées (69)

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Using Posterior-Based Features in Template Matching for Speech Recognition

Hervé Bourlard, Guillermo Aradilla

Given the availability of large speech corpora, as well as the increasing of memory and computational resources, the use of template matching approaches for automatic speech recognition (ASR) have recently attracted new attention. In such template-based ap ...

2006

Using Posterior-Based Features in Template Matching for Speech Recognition

Hervé Bourlard, Guillermo Aradilla

IDIAP2006

Multimodal Speaker Localization in a Probabilistic Framework

Jean-Philippe Thiran, Mihai Gurban

A multimodal probabilistic framework is proposed for the problem of finding the active speaker in a video sequence. We localize the current speaker's mouth in the image by using the video and the audio channels together. We propose a novel visual feature t ...

IEEE2006

Chemical shift correlations in disordered solids

David Lyndon Emsley

We show how two-dimensional chemical shift conditional probability distributions can be extracted from experimental NMR correlation spectra of disordered solids. We show that transverse dephasing times are of central importance in determining the resolutio ...

AMER CHEMICAL SOC2005

Gradient estimates of return distributions

Samy Bengio, Christos Dimitrakakis

We present a general method for maintaining estimates of the distribution of parameters in arbitrary models. This is then applied to the estimation of probability distributions over actions in value-based reinforcement learning. While this approach is simi ...

2005

Boosting word error rates

Samy Bengio, Christos Dimitrakakis

We apply boosting techniques to the problem of word error rate minimisation in speech recognition. This is achieved through a new definition of sample error for boosting and a training procedure for hidden Markov models. For this purpose we define a sample ...

2005

Boosting word error rates

Samy Bengio, Christos Dimitrakakis

2005

Estimates of Parameter Distributions for Optimal Action Selection

Samy Bengio, Christos Dimitrakakis

We present a general method for maintaining estimates of the distribution of parameters in arbitrary models. This is then applied to the estimation of probability distribution over actions in value-based reinforcement learning. While this approach is simil ...

IDIAP2004

Boosting word error rates

Samy Bengio, Christos Dimitrakakis

IDIAP2004

To code or not to code

Michael Christoph Gastpar

It is well known and surprising that the uncoded transmission of an independent and identically distributed Gaussian source across an additive white Gaussian noise channel is optimal: No amount of sophistication in the coding strategy can ever perform bett ...

EPFL2002