About
There has recently been a surge of interest in algebraic methods in machine learning. In no particular order, this includes: new approaches to ranking problems; the budding field of algebraic statistics; and various applications of non-commutative Fourier transforms.
The aim of the workshop is to bring together these distinct communities, explore connections, and showcase algebraic methods to the machine learning community at large. AML'08 is intended to be accessible to researchers with no prior exposure to abstract algebra. The program includes three short tutorials that will cover the basic concepts necessary for understanding cutting edge research in the field.
More information about workshop - http://www.gatsby.ucl.ac.uk/~risi/AML08/
Videos

Learning Parameters in Discrete Naive Bayes Models by Computing Fibers of the Pa...
Dec 20, 2008
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4980 views

Identity Management On Homogeneous spaces
Dec 20, 2008
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4029 views

Alternatives to the Discrete Fourier Transform
Dec 20, 2008
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9148 views

Toric Modification on Mixture Models
Dec 20, 2008
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3783 views

Algebraic statistics for random graph models: Markov bases and their uses
Dec 20, 2008
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8096 views

Algebraic statistics and contingency tables
Dec 20, 2008
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5194 views

Adaptive Fourier-Domain Inference on the Symmetric Group
Dec 20, 2008
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5630 views

Consistent Structured Estimation for Weighted Bipartite Matching
Dec 20, 2008
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5733 views

Stationary Subspace Analysis
Dec 20, 2008
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5816 views

Graph Helmholtzian and rank learning
Dec 20, 2008
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4659 views