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Improving speaker turn embedding by crossmodal transfer learning from face embedding

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Learning How To Recognize Faces In Heterogeneous Environments

Tiago De Freitas Pereira

Face recognition is a mature field in biometrics in which several systems have been proposed over the last three decades. Such systems are extremely reliable under controlled recording conditions and it has been deployed in the field in critical tasks, suc ...

EPFL2019

Graph-based image representation learning

Renata Khasanova

Though deep learning (DL) algorithms are very powerful for image processing tasks, they generally require a lot of data to reach their full potential. Furthermore, there is no straightforward way to impose various properties, given by the prior knowledge a ...

EPFL2019

Multimodal person recognition in audio-visual streams

Do Hoang Nam Le

Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...

EPFL2019

Learning embeddings: efficient algorithms and applications

Cijo Jose

Learning to embed data into a space where similar points are together and dissimilar points are far apart is a challenging machine learning problem. In this dissertation we study two learning scenarios that arise in the context of learning embeddings and o ...

École Polytechnique Fédérale de Lausanne2018

Learning embeddings: efficient algorithms and applications

Cijo Jose

EPFL2018

Diffusion gradient boosting for networked learning

Ali H. Sayed, Bicheng Ying

Using duality arguments from optimization theory, this work develops an effective distributed gradient boosting strategy for inference and classification by networked clusters of learners. By sharing local dual variables with their immediate neighbors thro ...

2017

Towards large scale multimedia indexing: A case study on person discovery in broadcast news

Jean-Marc Odobez

The rapid growth of multimedia databases and the human interest in their peers make indices representing the location and identity of people in audio-visual documents essential for searching archives. Person discovery in the absence of prior identity knowl ...

2017

Unsupervised Learning of Phase-Change-Based Neuromorphic Systems

Stanislaw Andrzej Wozniak

Neuromorphic systems provide brain-inspired methods of computing. In a neuromorphic architecture, inputs are processed by a network of neurons receiving operands through synaptic interconnections, tuned in the process of learning. Neurons act simultaneousl ...

EPFL2017

Building Word Embeddings for Solving Natural Language Processing

Rémi Philippe Lebret

Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...

École Polytechnique Fédérale de Lausanne2016

Word Embeddings for Natural Language Processing

Rémi Philippe Lebret

EPFL2016