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» Machine learning problems from optimization perspective
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104
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ALT
2009
Springer
15 years 6 months ago
Learning and Domain Adaptation
Domain adaptation is a fundamental learning problem where one wishes to use labeled data from one or several source domains to learn a hypothesis performing well on a different, y...
Yishay Mansour
167
Voted
ICMLA
2004
15 years 4 months ago
A new discrete binary particle swarm optimization based on learning automata
: The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social-psychological metaphor. A po...
Reza Rastegar, Mohammad Reza Meybodi, Kambiz Badie
110
Voted
MCS
2005
Springer
15 years 8 months ago
Ensemble of SVMs for Incremental Learning
Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
AAAI
2011
14 years 2 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal
124
Voted
COCOON
1995
Springer
15 years 6 months ago
Constructing Craig Interpolation Formulas
A Craig interpolant of two inconsistent theories is a formula which is true in one and false in the other. This paper gives an eificient method for constructing a Craig interpolant...
Guoxiang Huang