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» Sequential Instance-Based Learning
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ICML
1999
IEEE
14 years 8 months ago
Using Reinforcement Learning to Spider the Web Efficiently
Consider the task of exploring the Web in order to find pages of a particular kind or on a particular topic. This task arises in the construction of search engines and Web knowled...
Jason Rennie, Andrew McCallum
COLT
1994
Springer
13 years 12 months ago
An Optimal Parallel Algorithm for Learning DFA
: Sequential algorithms given by Angluin 1987 and Schapire 1992 learn deterministic nite automata DFA exactly from Membership and Equivalence queries. These algorithms are feasible...
José L. Balcázar, Josep Díaz,...
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
13 years 5 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
NN
2008
Springer
143views Neural Networks» more  NN 2008»
13 years 7 months ago
A batch ensemble approach to active learning with model selection
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
CORR
2007
Springer
170views Education» more  CORR 2007»
13 years 7 months ago
The structure of verbal sequences analyzed with unsupervised learning techniques
Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluab...
Catherine Recanati, Nicoleta Rogovschi, Youn&egrav...