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» Ensemble Algorithms in Reinforcement Learning
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DAWAK
2006
Springer
15 years 8 months ago
Mining Direct Marketing Data by Ensembles of Weak Learners and Rough Set Methods
This paper describes problem of prediction that is based on direct marketing data coming from Nationwide Products and Services Questionnaire (NPSQ) prepared by Polish division of A...
Jerzy Blaszczynski, Krzysztof Dembczynski, Wojciec...
ACL
2006
15 years 5 months ago
Semantic Parsing with Structured SVM Ensemble Classification Models
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...
Minh Le Nguyen, Akira Shimazu, Xuan Hieu Phan
NAACL
2010
15 years 2 months ago
Ensemble Models for Dependency Parsing: Cheap and Good?
Previous work on dependency parsing used various kinds of combination models but a systematic analysis and comparison of these approaches is lacking. In this paper we implemented ...
Mihai Surdeanu, Christopher D. Manning
BMCBI
2010
224views more  BMCBI 2010»
15 years 4 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
ML
2008
ACM
152views Machine Learning» more  ML 2008»
15 years 4 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...