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ICML
2004
IEEE
15 years 10 months ago
Online and batch learning of pseudo-metrics
We describe and analyze an online algorithm for supervised learning of pseudo-metrics. The algorithm receives pairs of instances and predicts their similarity according to a pseud...
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
15 years 4 months ago
Unsupervised learning of 3D object models from partial views
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
PKDD
2007
Springer
193views Data Mining» more  PKDD 2007»
15 years 4 months ago
Learning Multi-dimensional Functions: Gas Turbine Engine Modeling
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...
Chris Drummond
IJCNN
2006
IEEE
15 years 4 months ago
Learning to Segment Any Random Vector
— We propose a method that takes observations of a random vector as input, and learns to segment each observation into two disjoint parts. We show how to use the internal coheren...
Aapo Hyvärinen, Jukka Perkiö
CHI
1999
ACM
15 years 2 months ago
Learning and Performing by Exploration: Label Quality Measured by Latent Semantic Analysis
Models of learning and performing by exploration assume that the semantic distance between task descriptions and screen labels controls in part the usersÕ search strategies. Neve...
Rodolfo Soto