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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 7 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
JMLR
2006
99views more  JMLR 2006»
13 years 7 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
CIDR
2009
152views Algorithms» more  CIDR 2009»
13 years 8 months ago
Visualizing the robustness of query execution
In database query processing, actual run-time conditions (e.g., actual selectivities and actual available memory) very often differ from compile-time expectations of run-time cond...
Goetz Graefe, Harumi A. Kuno, Janet L. Wiener
CORR
2010
Springer
109views Education» more  CORR 2010»
13 years 7 months ago
An Ontology-based Context Aware System for Selective Dissemination of Information in a Digital Library
Users of Institutional Repositories and Digital Libraries are known by their needs for very specific information about one or more subjects. To characterize users profiles and offe...
Marisa R. De Giusti, Gonzalo L. Villarreal, Agust&...
SODA
2010
ACM
371views Algorithms» more  SODA 2010»
14 years 4 months ago
Online Learning with Queries
The online learning problem requires a player to iteratively choose an action in an unknown and changing environment. In the standard setting of this problem, the player has to ch...
Chao-Kai Chiang, Chi-Jen Lu