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» Learning by Experience Networks in Learning Organizations
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94
Voted
NIPS
2007
15 years 1 months ago
Multiple-Instance Active Learning
We present a framework for active learning in the multiple-instance (MI) setting. In an MI learning problem, instances are naturally organized into bags and it is the bags, instea...
Burr Settles, Mark Craven, Soumya Ray
101
Voted
ICML
2010
IEEE
15 years 1 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
88
Voted
IWINAC
2007
Springer
15 years 6 months ago
EDNA: Estimation of Dependency Networks Algorithm
One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...
José A. Gámez, Juan L. Mateo, Jose M...
IJCAI
1989
15 years 1 months ago
Integrating Knowledge-Based System and Neural Network Techniques for Robotic Skill Acquisition
This paper describes an approach to robotic control that is patterned after models of human skill acquisition. The intent is to develop robots capable of learning how to accomplis...
David Handelman, Stephen Lane, Jack Gelfand
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 28 days ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...