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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4972 views

Identity Management On Homogeneous spaces
Dec 20, 2008
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4021 views

Alternatives to the Discrete Fourier Transform
Dec 20, 2008
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9131 views

Toric Modification on Mixture Models
Dec 20, 2008
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3777 views

Algebraic statistics for random graph models: Markov bases and their uses
Dec 20, 2008
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8081 views

Algebraic statistics and contingency tables
Dec 20, 2008
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5186 views

Adaptive Fourier-Domain Inference on the Symmetric Group
Dec 20, 2008
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5606 views

Consistent Structured Estimation for Weighted Bipartite Matching
Dec 20, 2008
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5724 views

Stationary Subspace Analysis
Dec 20, 2008
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5807 views

Graph Helmholtzian and rank learning
Dec 20, 2008
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4649 views