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» On-line Algorithms in Machine Learning
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COLT
2007
Springer
15 years 10 months ago
Learning Permutations with Exponential Weights
We give an algorithm for the on-line learning of permutations. The algorithm maintains its uncertainty about the target permutation as a doubly stochastic weight matrix, and makes...
David P. Helmbold, Manfred K. Warmuth
ECML
2007
Springer
15 years 10 months ago
Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search
We discuss how to learn non-recursive directed probabilistic logical models from relational data. This problem has been tackled before by upgrading the structure-search algorithm i...
Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendr...
ICML
2008
IEEE
16 years 4 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh
142
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ICML
2005
IEEE
16 years 4 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...

Book
412views
17 years 2 months ago
Algorithms for Clustering Data
"Cluster analysis is an important technique in the rapidly growing field known as exploratory data analysis and is being applied in a variety of engineering and scientific dis...
A. K. Jain, R. C. Dubes