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NIPS
2001
15 years 19 days ago
Learning Lateral Interactions for Feature Binding and Sensory Segmentation
We present a new approach to the supervised learning of lateral interactions for the competitive layer model (CLM) dynamic feature binding architecture. The method is based on con...
Heiko Wersing
CORR
2006
Springer
99views Education» more  CORR 2006»
14 years 11 months ago
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Jon Feldman, Ryan O'Donnell, Rocco A. Servedio
ICML
2007
IEEE
16 years 1 days ago
Parameter learning for relational Bayesian networks
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Manfred Jaeger
ICML
2006
IEEE
16 years 1 days ago
An analysis of graph cut size for transductive learning
I consider the setting of transductive learning of vertex labels in graphs, in which a graph with n vertices is sampled according to some unknown distribution; there is a true lab...
Steve Hanneke
ICML
2000
IEEE
16 years 1 days ago
Learning Subjective Functions with Large Margins
In manyoptimization and decision problems the objective function can be expressed as a linear combinationof competingcriteria, the weights of whichspecify the relative importanceo...
Claude-Nicolas Fiechter, Seth Rogers