Discriminative modeling of spectro-temporal evolution of covert visuospatial attention for BCI
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This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...
This work proposes a new approach to the retrieval of images from text queries. Contrasting with previous work, this method relies on a discriminative model: the parameters are selected in order to minimize a loss related to the ranking performance of the ...
The objective of this thesis is to develop probabilistic graphical models for analyzing human interaction in meetings based on multimodel cues. We use meeting as a study case of human interactions since research shows that high complexity information is mo ...
This paper proposes a discriminative approach to template-based keyword detection. We introduce a method to learn the distance used to compare acoustic frames, a crucial element for template matching approaches. The proposed algorithm estimates the distanc ...
This paper introduces a discriminative model for the retrieval of images from text queries. Our approach formalizes the retrieval task as a ranking problem, and introduces a learning procedure optimizing a criterion related to the ranking performance. The ...
The objective of this thesis is to develop probabilistic graphical models for analyzing human interaction in meetings based on multimodel cues. We use meeting as a study case of human interactions since research shows that high complexity information is mo ...
This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...
This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval performance of the model. For that purpose, we rely on a ranking loss which ha ...
The objective of this thesis is to develop probabilistic graphical models for analyzing human interaction in meetings based on multimodel cues. We use meeting as a study case of human interactions since research shows that high complexity information is mo ...
This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval performance of the model. For that purpose, we rely on a ranking loss which ha ...