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TSP
2010
13 years 4 months ago
Recursive least squares dictionary learning algorithm
We present the Recursive Least Squares Dictionary Learning Algorithm, RLSDLA, which can be used for learning overcomplete dictionaries for sparse signal representation. Most Dicti...
Karl Skretting, Kjersti Engan
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
14 years 3 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
AMAI
2004
Springer
14 years 3 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
JMLR
2002
111views more  JMLR 2002»
13 years 9 months ago
The Learning-Curve Sampling Method Applied to Model-Based Clustering
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Christopher Meek, Bo Thiesson, David Heckerman
ICDM
2009
IEEE
169views Data Mining» more  ICDM 2009»
13 years 7 months ago
Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification
There are many clustering tasks which are closely related in the real world, e.g. clustering the web pages of different universities. However, existing clustering approaches neglec...
Quanquan Gu, Jie Zhou