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A Discriminative Kernel-based Model to Rank Images from Text Queries

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Object Category Detection using Audio-visual Cues

Barbara Caputo, Jie Luo

Categorization is one of the fundamental building blocks of cognitive systems. Object categorization has traditionally been addressed in the vision domain, even though cognitive agents are intrinsically multimodal. Indeed, biological systems combine severa ...

IDIAP2007

Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods

Matthias Seeger

We propose a highly efficient framework for kernel multi-class models with a large and structured set of classes. Kernel parameters are learned automatically by maximizing the cross-validation log likelihood, and predictive probabilities are estimated. We ...

2007

Melanoma Recognition Using Representative and Discriminative Kernel Classifiers

Barbara Caputo, Tatiana Tommasi

Malignant melanoma is the most deadly for of skin lesion. Early diagnosis is of critical importance to patient survival. Visual recognition algorithms could potentially be of great help for physicians in a computer assisted diagnosis system. Previous work ...

2006

Learning to Retrieve Images from Text Queries with a Discriminative Model

Samy Bengio, David Grangier, Florent Monay Michaud

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 ...

2006

Learning to Retrieve Images from Text Queries with a Discriminative Model

Samy Bengio, David Grangier, Florent Monay Michaud

IDIAP2006

Prior Knowledge in Kernel Methods

Alexei Pozdnoukhov

Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...

École Polytechnique Fédérale de Lausanne2006

Prior knowledge in Kernel methods

Alexei Pozdnoukhov

EPFL2006

Towards a Robust BCI: Error Potentials and Online Learning

José del Rocio Millán Ruiz, Anna Buttfield, Pierre Ferrez

Recent advances in the field of Brain-Computer Interfaces (BCIs) have shown that BCIs have the potential to provide a powerful new channel of communication, completely independent of muscular and nervous systems. However, while there have been successful l ...

2006

Melanoma Recognition using Kernel Classifiers

Barbara Caputo, Tatiana Tommasi

Melanoma is the most deadly skin cancer. Early diagnosis is a current challenge for clinicians. Current algorithms for skin lesions classification focus mostly on segmentation and feature extraction. This paper instead puts the emphasis on the learning pro ...

IDIAP2006

Kernel Methods for Melanoma Recognition

Barbara Caputo, Tatiana Tommasi

2006