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STOC
2003
ACM
122views Algorithms» more  STOC 2003»
14 years 8 months ago
Learning juntas
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
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
CVIU
2004
115views more  CVIU 2004»
13 years 7 months ago
Dynamic learning from multiple examples for semantic object segmentation and search
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...
Yaowu Xu, Eli Saber, A. Murat Tekalp
JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
The Coding Divergence for Measuring the Complexity of Separating Two Sets
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
Mahito Sugiyama, Akihiro Yamamoto
RSCTC
2000
Springer
185views Fuzzy Logic» more  RSCTC 2000»
13 years 11 months ago
A Comparison of Several Approaches to Missing Attribute Values in Data Mining
: In the paper nine different approaches to missing attribute values are presented and compared. Ten input data files were used to investigate the performance of the nine methods t...
Jerzy W. Grzymala-Busse, Ming Hu