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17 years 3 months ago
Machine Learning, Neural and Statistical Classification
This book covers several topics such as Classification, Classical Statistical Methods, Modern Statistical Techniques, Machine Learning of Rules and Trees, Neural Networks Methods ...
Ellis Horwood
133
Voted
IEAAIE
2001
Springer
15 years 9 months ago
On the Relationship between Learning Capability and the Boltzmann-Formula
In this paper a combined use of reinforcement learning and simulated annealing is treated. Most of the simulated annealing methods suggest using heuristic temperature bounds as the...
Péter Stefán, Laszlo Monostori
ICML
2001
IEEE
16 years 5 months ago
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other popular techniques that instead aim to reduce versio...
Nicholas Roy, Andrew McCallum
138
Voted
ATAL
2005
Springer
15 years 10 months ago
Behavior transfer for value-function-based reinforcement learning
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...
Matthew E. Taylor, Peter Stone
155
Voted
LOCA
2009
Springer
15 years 9 months ago
Activity Recognition from Sparsely Labeled Data Using Multi-Instance Learning
Abstract. Activity recognition has attracted increasing attention in recent years due to its potential to enable a number of compelling contextaware applications. As most approache...
Maja Stikic, Bernt Schiele