SRL2004: Statistical Relational Learning and
its Connections to Other Fields




Contact Information
Mailing List


8:30-8:50 - Welcome, Opening Remarks, Introduction

8:50 - 9:20 - Invited Talk I
David Heckerman: Probabilistic Entity-Relationship Models, PRMs, and Plate Models

9:20 - 9:50 - Invited Talk II
David Poole: Relations, generalizations and the reference-class problem: A logic programming / Bayesian perspective

9:50 - 10:00 - discussion

10.00-10:30 coffee break

Markov Logic: A Unifying Framework for Statistical Relational Learning
Pedro Domingos and Matthew Richardson

BLOG: Relational Modeling with Unknown Objects
Brian Milch, Bhaskara Marthi and Stuart Russell

Autocorrelation and Relational Learning: Challenges and Opportunities
Jennifer Neville and Ozgur Simsek and David Jensen

11:30-12:15 Poster Highlights (2 minutes each)


A System for Feature Discovery and Selection in Probabilistic Relational Models
Eric Altendorf and Bruce D'Ambrosio

A Comparison of Inference Techniques for Semi-supervised Clustering with Hidden Markov Random Fields
Mikhail Bilenko and Sugato Basu

Using neural networks for relational learning
Hendrik Blockeel and Werner Uwents

Learning Spatial Configuration Models Using Modified Dirichlet Priors
Matthew Boutell, Christopher Brown and Jiebo Luo

Relational Markov Networks for Collective Information Extraction
Razvan Bunescu and Ray Mooney

Clustering in Relational Biological Data
Aynu Dayanik and Craig G. Nevill-Manning

Relational Decision Networks
William Hsu and Roby Joehanes

Hierarchical Probabilistic Relational Models for Collaborative Filtering
Jack Newton and Russell Greiner

Cluster-based Concept Invention for Statistical Relational Learning
Alexandrin Popscul and Lyle Ungar

Learning Complex Motion Structures
Fabio Ramos and Hugh Durrant-Whyte

A Dyanmic Programming Approach to Parameter Learning of Generative Models with Failure
Taisuke Sato and Yoshitaka Kameya

Using Random Forests for Relational Learning
Anneleen Van Assche, Celine Vens, Hendrik BLockeel and Saso Dzeroski

A Regularization Framework for Learning from Relational Data
Dengyong Zhou and Bernhard Scholkopf

Web Page Organization and Visualization Using Generative Topographic Mapping - A Pilot Study
Xiao-Feng Zhang, Chak-Man Lam and WIlliam Cheung

Playing Multiple Roles: Discovering Overlapping Roles in Social Networks
Alicia Wolfe and David Jensen

12:15 - 2:30 - Poster session/ Lunch

2:30-3:00 - Invited Talk III
Mark Handcock: Statistical Models for Social Networks

3:00-3:30 - Invited Talk IV
Dan Huttenlocher: Pictorial Structure Models for Visual Recognition

3.30 - 4:00 coffee

4:00 - 4:30 - Invited Talk V
Michael Collins

4:30-5.30 - Discussion and Wrap Up