Meteor: Meta-learning connecting earth problems observed from space
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Our brain continuously self-organizes to construct and maintain an internal representation of the world based on the information arriving through sensory stimuli. Remarkably, cortical areas related to different sensory modalities appear to share the same f ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...
Many classes of objects can now be successfully detected with statistical machine learning techniques. Faces, cars and pedestrians, have all been detected with low error rates by learning their appearance in a highly generic manner from extensive training ...
Machine Learning techniques play an increasingly vital role in the analysis of Biomedical imagery, as in all other areas of Computer Vision. However, in this specific context, they suffer from the fact that experimental conditions and protocols change ofte ...
The presence of a bias in each image data collection has recently attracted a lot of attention in the computer vision community showing the limits in generalization of any learning method trained on a specific dataset. At the same time, with the rapid deve ...
We study the binary transfer learning problem, focusing on how to select sources from a large pool and how to combine them to yield a good performance on a target task. In particular, we consider the transfer learning setting where one does not have direct ...
Networks are everywhere and we are confronted with many networks in our daily life. Networks such as Internet, World Wide Web, social, biological and economical networks have been subject to extensive studies in the last decade. The volume of publications ...
The vast majority of transfer learning methods proposed in the visual recognition domain over the last years ad- dresses the problem of object category detection, assuming a strong control over the priors from which transfer is done. This is a strict condi ...
The vast majority of transfer learning methods proposed in the visual recognition domain over the last years ad- dresses the problem of object category detection, assuming a strong control over the priors from which transfer is done. This is a strict condi ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...