Publication

Evaluation of a probabilistic approach to learn and reproduce gestures by imitation

Publications associées (23)

Lower Bounds on Active Learning for Graphical Model Selection

We consider the problem of estimating the underlying graph associated with a Markov random field, with the added twist that the decoding algorithm can iteratively choose which subsets of nodes to sample based on the previous samples, resulting in an active ...

2017

Low-rank and Sparse Soft Targets to Learn Better DNN Acoustic Models

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

Conventional deep neural networks (DNN) for speech acoustic modeling rely on Gaussian mixture models (GMM) and hidden Markov model (HMM) to obtain binary class labels as the targets for DNN training. Subword classes in speech recognition systems correspond ...

Ieee2017

Finding Steady States of Communicating Markov Processes Combining Aggregation/Disaggregation with Tensor Techniques

Francisco Santos Paredes Quartin de Macedo

Stochastic models for interacting processes feature a dimensionality that grows exponentially with the number of processes. This state space explosion severely impairs the use of standard methods for the numerical analysis of such Markov chains. In this wo ...

Springer Int Publishing Ag2016