Special Session on Advances in Algebraic Statistics

AMS 2010 Spring Southeastern Sectional Meeting Lexington, KY, March 27th-28th, 2010.

Algebraic Statistics is the field focused on the applications of algebraic geometry and its computational tools in the study of statistical models. Areas of interest include categorial data analysis, experimental design, graphical models, maximum likelihood estimation, and Bayesian methods. Also recent work shows that we can apply theory in algebraic statistics to developing algorithms for problems in biology and also problems in computational biology enhance research in algebraic statistics. This session is meant to provide another meeting point for students and leaders in the field, continuing the tradition of focused meetings we have had in recent years.

Organizers

Sonja Petrovic, University of Illinois, Chicago

Ruriko Yoshida, University of Kentucky

Abstract submission

The deadline for abstract submission is January 26, 2010 (DATE CHANGED). LINK

Place

CB204 University of Kentucky Lexington KY

Restaurants

Restaurants in Lexington LINK

Events and extra information

Registration at Registration will start at 7:30am on Saturday March 27th outside room CB118.

Reception Saturday March 27th (6:15-7:45pm) at the King Alumni House

Welcome party at Yoshida's house at 7pm on March 26th Friday

Slides of talks

Slides of all talks (Coming up on Thurs April 1st 2010)

Confirmed speakers

• Enrico Carlini, Dipartimento di Matematica (DIMAT), Politecnico di Torino Parameterization of mixture of independence models
• Alexander Engstrom, Mathematics Department, University of California, Berkeley Ideals of Graph Homomorphisms
• Steve Fienberg, Statistics Department, Carnegie Mellon University Large Sparse Data and Algebraic Statistics: Is There a Connection?
• Roberto Fontana, Dipartimento di Matematica (DIMAT), Politecnico di Torino Algebraic generation of Orthogonal Fractional Factorial Designs
• Luis David Garcia-Puente, Department of Mathematics and Statistics, Sam Houston State University Identifiability of Gaussian graphical model
• David Haws, Statistics Department, University of Kentucky Identifying Outlier Gene Trees: Gene Tree Distributions and Support Vector Machinery
• Valerie Hower, Mathematics Department, University of California, Berkeley Using sequence coverage statistics to determine protein binding sites in a genome
• Thomas Kahle, Max Planck Institute for Mathematics in the Sciences, Binomial Edge Ideals and Conditional Independence
• Anna Magdalena Kedzierska, University of Catalonia, Barcelona Model selection for mixture models
• Shaowei Lin, Mathematics Department, University of California, Berkeley Asymptotic Approximation of Marginal Likelihood Integrals.
• Helene Massam, Department of Mathematics and Statistics, York University The geometry of hierarchical discrete loglinear models
• Jason Morton, Mathematics and Statistics Department, Penn State University Geometry of Restricted Boltzmann Machines
• Fabio Rapallo, Dipartimento di Scienze e Tecnologie Avanzate Universita' del Piemonte Orientale Study of diagonal-effect models as toric and mixture models
• Megan Owen, Mathematics Department, North Carolina State University Averaging Metric Trees
• Alessandro Rinaldo, Statistics Department, Carnegie Mellon University On the Geometry of Discrete Exponential Families with Application to Exponential Random Graph Models
• Alexander Schoenhuth, Mathematics Department, University of California, Berkeley How to identify hidden Markov processes---an algebraic statistical answer
• Aleksandra Slavkovic, Statistics Department, Penn State University Algebraic statistics framework for causal inference and data privacy with discrete data
• Erik Stokes, Mathematics Department, Michigan Tech Hierarchical Models, Markov Bases and Stanley-Reisner Ideals
• Seth Sullivant, Mathematics Department, North Carolina State University Identifiability of Phylogenetic Mixture Models
• Akimichi Takemura, Department of Mathematical Informatics, The University of Tokyo Hierarchical subspace models for contingency tables
• Caroline Uhler, Statistics Department, University of California, Berkeley Semidefinite matrix completion and Gaussian graphical models
• Marlos Viana, University of Illinois at Chicago Eye Center Spectral Analysis of Dihedral Data
• Han Xiao, Statistics Department, University of Chicago Smoothness of Gaussian conditional independence models

Schedule

SATURDAY

• AM (8:30am-11am)

  Seth Sullivant (8:30)
  Alexander Engstrom (9:00)
  Alessandro Rinaldo (9:30)
  Shaowei Lin (10:00)
  Luis David Garcia-Puente (10:30)
  

• PM (2:30pm-6pm)

  Jason Morton (2:30)
  Roberto Fontana (3:00)
  Megan Owen (3:30)
  David Haws (4:00)
  Caroline Uhler (4:30)
  Helene Massam (5:00)
  Aleksandra Slavkovic (5:30)
  

SUNDAY

• AM (8am-11am)

  Akimichi Takemura (8:00)
  Valerie Hower (8:30)
  Erik Stokes (9:00)
  Fabio Rapallo (9:30)
  Han Xiao (10:00)
  Steve Fienberg (10:30)
  

• PM (2:30pm-5:00pm)

  Anna Kedzierska (2:30)
  Marlos Viana (3:00)
  Enrico Carlini (3:30)
  Thomas Kahle (4:00)
  Alexander Schoenhuth (4:30)
  

Links

• AMS site
• Math Department webpage for AMS meeting SITE
• Information on Housing PDF