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» Algorithm Selection using Reinforcement Learning
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SBBD
2000
168views Database» more  SBBD 2000»
15 years 4 months ago
Fast Feature Selection Using Fractal Dimension
Dimensionalitycurse and dimensionalityreduction are two issues that have retained highinterest for data mining, machine learning, multimedia indexing, and clustering. We present a...
Caetano Traina Jr., Agma J. M. Traina, Leejay Wu, ...
ICML
1999
IEEE
16 years 3 months ago
Distributed Value Functions
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore...
CIKM
1999
Springer
15 years 7 months ago
Training a Selection Function for Extraction
In this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence ...
Chin-Yew Lin
COLING
2010
14 years 10 months ago
Active Deep Networks for Semi-Supervised Sentiment Classification
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
Shusen Zhou, Qingcai Chen, Xiaolong Wang
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
16 years 3 months ago
Reasoning about sets using redescription mining
Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of associa...
Mohammed Javeed Zaki, Naren Ramakrishnan