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GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
14 years 16 days ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson
HT
2010
ACM
13 years 11 months ago
Assessing users' interactions for clustering web documents: a pragmatic approach
In this paper we are interested in describing Web pages by how users interact within their contents. Thus, an alternate but complementary way of labelling and classifying Web docu...
Luis A. Leiva, Enrique Vidal
HIS
2004
13 years 10 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 10 months ago
An evolutionary approach for competency-based curriculum sequencing
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Sequencing is usually per...
Luis de Marcos, José-Javier Martínez...
ICML
2010
IEEE
13 years 10 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein