AIM 2011 Singular Learning Theory slides

Semester: Fall 2011
Organizers: Russel Steele, Bernd Sturmfels, and Sumio Watanabe
Location: American Institute of Mathematics, Palo Alto, California
Date: Dec 12 – 16, 2011

This page hosts a collection of slides, links, and other resources relevant to the 2011 AIM workshop on Singular Learning Theory.

Day	Speaker	Title, slides and links
Monday	Mathias Drton	Reduced Rank Regression
Monday	Shaowei Lin	Singular Learning Theory – a view from algebraic geometry see also: Asymptotic approximation of marginal likelihood ratios
Tuesday	Anton Leykin	Computational algebraic geometry – Learning coefficients via symbolic and numerical methods see also: a short Macaulay2 demonstration
Tuesday	Sumio Watanabe	Algebraic geometry and model selection
Wednesday	Franz Kiraly	Approximate algebra for parametric estimateion
Wednesday	Helene Massam	The geometry of discrete loglinear models and Bayes factors
Thursday	Martyn Plummer	Bayesian model selection
Thursday	Miki Aoyagi	Consideration on singularities in learning theory and real log canonical tresholds
Friday	Piotr Zwiernik	Asymptotic behaviour of the marginal likelihood integral for general Markov models
Friday	Alexander Schliep	Model selection in bioinformatics: three short stories

Participants:

• Miki Aoyagi
• Arnon Boneh
• Andrew Critch
• Mathias Drton
• Luis Garcia-Puente
• Helene Gehrmann
• Elizabeth Gross
• Vishesh Karwa
• Franz Kiraly
• Gerard Letac
• Anton Leykin
• Shaowei Lin
• Helene Massam
• Guido Montufar
• Jason Morton
• Luis Pericchi
• Sonja Petrovic
• Martyn Plummer
• Jose Rodriguez
• Alexander Schliep
• Aleksandra Slavkovic
• Russell Steele
• Bernd Sturmfels
• Seth Sullivant
• Caroline Uhler
• Sumio Watanabe
• Jing Xi
• Yongli Zhang
• Piotr Zwiernik