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CORR
2007
Springer
104views Education» more  CORR 2007»
13 years 7 months ago
Separable convex optimization problems with linear ascending constraints
Separable convex optimization problems with linear ascending inequality and equality constraints are addressed in this paper. An algorithm that explicitly characterizes the optimum...
Arun Padakandla, Rajesh Sundaresan
JMLR
2012
11 years 10 months ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
ICML
2006
IEEE
14 years 1 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
IVC
2007
184views more  IVC 2007»
13 years 7 months ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless