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ECML
2004
Springer
16 years 26 days ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
184
Voted
ECCV
2010
Springer
16 years 24 days ago
Convolutional learning of spatio-temporal features
Abstract. We address the problem of learning good features for understanding video data. We introduce a model that learns latent representations of image sequences from pairs of su...
ICALT
2003
IEEE
16 years 22 days ago
Online Self-Assessment as a Learning Method
Algorithms and Programming Languages is a core subject in the BS Degree in Mathematics at the authors’ university. Some of the students are very interested in computer programmi...
Daniel Gayo-Avello, Hortensia Fernández-Cue...
191
Voted
ILP
2001
Springer
15 years 12 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
ICDAR
1999
IEEE
15 years 11 months ago
Cursive Character Detection using Incremental Learning
This paper describes a new hybrid architecture for an artificial neural network classifier that enables incremental learning. The learning algorithm of the proposed architecture d...
Jean-François Hébert, Marc Parizeau,...