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» Learning Algorithms for Domain Adaptation
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ICML
2000
IEEE
16 years 3 months ago
Solving the Multiple-Instance Problem: A Lazy Learning Approach
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Jun Wang, Jean-Daniel Zucker
ISCAS
2003
IEEE
117views Hardware» more  ISCAS 2003»
15 years 8 months ago
Learning temporal correlations in biologically-inspired aVLSI
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Adria Bofill-i-Petit, Alan F. Murray
122
Voted
ECAL
2005
Springer
15 years 8 months ago
A Dynamical Systems Approach to Learning: A Frequency-Adaptive Hopper Robot
We present an example of the dynamical systems approach to learning and adaptation. Our goal is to explore how both control and learning can be embedded into a single dynamical sys...
Jonas Buchli, Ludovic Righetti, Auke Jan Ijspeert
ICCBR
2005
Springer
15 years 8 months ago
Learning Semantic Annotations for Textual Cases
Abstract. In this paper, we propose an approach to attach semantic annotations to textual cases for their representation. To achieve this goal, a framework that combines machine le...
Eni Mustafaraj, Martin Hoof, Bernd Freisleben
CEC
2009
IEEE
15 years 9 months ago
An adaptive learning particle swarm optimizer for function optimization
— Traditional particle swarm optimization (PSO) suffers from the premature convergence problem, which usually results in PSO being trapped in local optima. This paper presents an...
Changhe Li, Shengxiang Yang