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Bio-inspired Reflex System for Learning Visual Information for Resilient Robotic Manipulation

Publications associées (124)

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Composite Kernel Learning

The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning (MKL) enables to learn the kernel, from an ensemble of ...

Omnipress2008

Composite Kernel Learning

IDIAP2008

Perceptual learning of bisection stimuli under roving: slow and largely specific

Michael Herzog, Thomas Otto

In perceptual learning, performance often improves within a short time if only one stimulus variant is presented, such as a line bisection stimulus with one outer-line-distance. However, performance stagnates if two bisection stimuli with two outer-line-di ...

Association for Research in Vision and Ophthalmology2008

When does roving disrupt perceptual learning?

Michael Herzog, Elisa Tartaglia, Carl Kristoffer Aberg

Training with one type of a visual stimulus usually improves performance. When observers train with two or more stimulus types presented in random order (so-called roving), performance improves for certain stimulus types but not for others. To understand w ...

2008

In search of the neural circuits of intrinsic motivation

Frédéric Kaplan

Children seem to acquire new know-how in a continuous and open-ended manner. In this paper, we hypothesize that an intrinsic motivation to progress in learning is at the origins of the remarkable structure of children’s developmental trajectories. In this ...

2007

Behaviour design in microrobots

Masoud Asadpour

In order to verify models of collective behaviors of animals, robots could be manipulated to implement the model and interact with real animals in a mixed-society. This thesis describes design of the behavioral hierarchy of a miniature robot, that is able ...

EPFL2006

MOTIF: AN EFFICIENT ALGORITHM FOR LEARNING TRANSLATION INVARIANT DICTIONARIES

Pierre Vandergheynst, Rémi Gribonval, Philippe Jost

The performances of approximation using redundant expansions rely on having dictionaries adapted to the signals. In natural high-dimensional data, the statistical dependencies are, most of the time, not obvious. Learning fundamental patterns is an alternat ...

2006

Learning Multi-Modal Dictionaries: Application to Audiovisual Data

Pierre Vandergheynst, Rémi Gribonval, Gianluca Monaci, Philippe Jost

This paper presents a methodology for extracting meaningful synchronous structures from multi-modal signals. Simultaneous processing of multi-modal data can reveal information that is unavailable when handling the sources separately. However, in natural hi ...

2006

Pattern Recognition from One Example by Chopping

François Fleuret

We investigate the learning of the appearance of an object from a single image of it. Instead of using a large number of pictures of an object to be recognized, we use pictures of other objects to learn invariance to noise and variations in pose and illumi ...

2005

Learning Objectives and Uncertainty Resolution: An Examination of the Structure of Corporate Venture Capital Relationships

Anu Wadhwa

The search for external knowledge must necessarily be accompanied by effective organizational learning. The effectiveness of learning is dependent on quite dissimilar factors based on whether the learning objective is explorative or exploitative. Moreover, ...

2005