NIPS Workshop on Algebraic and Combinatorial Methods in Machine Learning, Whistler 2008
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/
Identity Management On Homogeneous spaces
Dec 20, 2008 4037 views
Algebraic statistics and contingency tables
Dec 20, 2008 5203 views
Alternatives to the Discrete Fourier Transform
Dec 20, 2008 9164 views
Consistent Structured Estimation for Weighted Bipartite Matching
Dec 20, 2008 5748 views
Stationary Subspace Analysis
Dec 20, 2008 5828 views
Adaptive Fourier-Domain Inference on the Symmetric Group
Dec 20, 2008 5645 views
Toric Modification on Mixture Models
Dec 20, 2008 3792 views
Graph Helmholtzian and rank learning
Dec 20, 2008 4670 views
Learning Parameters in Discrete Naive Bayes Models by Computing Fibers of the Pa...
Dec 20, 2008 4989 views
Algebraic statistics for random graph models: Markov bases and their uses
Dec 20, 2008 8113 views
