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» Machine Learning by Function Decomposition
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ICML
2010
IEEE
15 years 3 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
ICALT
2007
IEEE
15 years 8 months ago
The Design of e-Learning Environment Oriented for Personalized Adaptability
A design of e-Learning environment is described for personalized adaptability. At first, we explain the whole system of our learning management system, WebClass RAPSODY, which has...
Toshie Ninomiya, Ken Nakayama, Miyuki Shimizu, Fum...
COLT
1989
Springer
15 years 6 months ago
Learning in the Presence of Inaccurate Information
The present paper considers the effects of introducing inaccuracies in a learner’s environment in Gold’s learning model of identification in the limit. Three kinds of inaccu...
Mark A. Fulk, Sanjay Jain
EVOW
2006
Springer
15 years 5 months ago
Functional Classification of G-Protein Coupled Receptors, Based on Their Specific Ligand Coupling Patterns
Functional identification of G-Protein Coupled Receptors (GPCRs) is one of the current focus areas of pharmaceutical research. Although thousands of GPCR sequences are known, many ...
Burcu Bakir, Osman Ugur Sezerman
ADMA
2005
Springer
149views Data Mining» more  ADMA 2005»
15 years 7 months ago
A New Support Vector Machine for Data Mining
Abstract. This paper proposes a new support vector machine (SVM) with a robust loss function for data mining. Its dual optimal formation is also constructed. A gradient based algor...
Haoran Zhang, Xiaodong Wang, Changjiang Zhang, Xiu...