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Robust Distributed Learning and Robust Learning Machines (Research Statement)

Publications associées (75)

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Temporal patterning of 'unlearnable' stimuli types does not always enable learning

Michael Herzog, Carl Kristoffer Aberg

Presenting two or more stimulus types randomly interleaved, so-called roving stimuli, disrupts perceptual learning in many paradigms. It was recently reported that learning with disrupting stimuli types is possible when stimuli are presented in an alternat ...

2009

Anesthesia prevents auditory perceptual learning

Michael Herzog, Alain Farron, Elisa Tartaglia, Carl Kristoffer Aberg

BACKGROUND: An auditory perceptual learning paradigm was used to investigate whether implicit memories are formed during general anesthesia. METHODS: Eighty-seven patients who had an American Society of Anesthesiologists physical status of I-III and were s ...

Lippincott, Williams & Wilkins2009

Spike detection algorithm improvement, spike waveforms projections with PCA and hierarchical classification

Diego Ghezzi

Definition of single spikes from multiunit spike trains plays a critical role in neurophysiology and in neuroengineering. Moreover, long period analysis are needed to study synaptic plasticity effects and observe the long and medium term development on whi ...

IEEE2008

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

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

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

Coding and Learning of behavioral sequences

Wulfram Gerstner, Henry Markram

A major challenge to understanding behavior is how the nervous system allows the learning of behavioral sequences that can occur over arbitrary timescales, ranging from milliseconds up to seconds, using a fixed millisecond learning rule. This article descr ...

2004