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CORR
2010
Springer
101views Education» more  CORR 2010»
15 years 2 months ago
Online Learning: Random Averages, Combinatorial Parameters, and Learnability
We develop a theory of online learning by defining several complexity measures. Among them are analogues of Rademacher complexity, covering numbers and fatshattering dimension fro...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
ICML
2007
IEEE
16 years 3 months ago
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers
In this paper we present a novel algorithm, CarpeDiem. It significantly improves on the time complexity of Viterbi algorithm, preserving the optimality of the result. This fact ha...
Roberto Esposito, Daniele P. Radicioni
ICML
1997
IEEE
15 years 6 months ago
Efficient Feature Selection in Conceptual Clustering
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
Mark Devaney, Ashwin Ram
DIS
2009
Springer
15 years 9 months ago
MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
Yasser El-Manzalawy, Vasant Honavar
IROS
2006
IEEE
190views Robotics» more  IROS 2006»
15 years 8 months ago
Q-RAN: A Constructive Reinforcement Learning Approach for Robot Behavior Learning
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
Jun Li, Achim J. Lilienthal, Tomás Mart&iac...