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» Learning with the Set Covering Machine
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ICML
2008
IEEE
14 years 8 months ago
SVM optimization: inverse dependence on training set size
We discuss how the runtime of SVM optimization should decrease as the size of the training data increases. We present theoretical and empirical results demonstrating how a simple ...
Shai Shalev-Shwartz, Nathan Srebro
ALT
2006
Springer
14 years 4 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
IJCAI
2007
13 years 9 months ago
A Fully Connectionist Model Generator for Covered First-Order Logic Programs
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Sebastian Bader, Pascal Hitzler, Steffen Höll...
AAAI
2008
13 years 10 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
ICALT
2006
IEEE
14 years 1 months ago
Mobile Learning: Is Anytime + Anywhere = Always Online?
The new e-learning trend, called mobile learning opens variety of questions to solve. To allow access to learning content anytime and anyplace a technique called hoarding is somet...
Anna Trifonova, Marco Ronchetti