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ICML
2004
IEEE
15 years 10 months ago
Learning to learn with the informative vector machine
This paper describes an ecient method for learning the parameters of a Gaussian process (GP). The parameters are learned from multiple tasks which are assumed to have been drawn ...
Neil D. Lawrence, John C. Platt
PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
15 years 11 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano
137
Voted
STACS
1999
Springer
15 years 8 months ago
A Complete and Tight Average-Case Analysis of Learning Monomials
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Rüdiger Reischuk, Thomas Zeugmann
IVC
2010
128views more  IVC 2010»
15 years 3 months ago
Online kernel density estimation for interactive learning
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...
Matej Kristan, Danijel Skocaj, Ales Leonardis
142
Voted
BMCBI
2008
114views more  BMCBI 2008»
15 years 4 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...