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ICML
2004
IEEE
16 years 4 months ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
136
Voted
GECCO
2004
Springer
122views Optimization» more  GECCO 2004»
15 years 9 months ago
Gradient-Based Learning Updates Improve XCS Performance in Multistep Problems
This paper introduces a gradient-based reward prediction update mechanism to the XCS classifier system as applied in neuralnetwork type learning and function approximation mechani...
Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
135
Voted
GCB
2003
Springer
164views Biometrics» more  GCB 2003»
15 years 8 months ago
Integrative machine learning approach for multi-class SCOP protein fold classification
: Classification and prediction of protein structure has been a central research theme in structural bioinformatics. Due to the imbalanced distribution of proteins over multi SCOP ...
Aik Choon Tan, David Gilbert, Yves Deville
152
Voted
COLT
2006
Springer
15 years 7 months ago
Online Learning Meets Optimization in the Dual
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Shai Shalev-Shwartz, Yoram Singer
114
Voted
ESANN
2003
15 years 5 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre