![]() |
SRL2004: Statistical Relational Learning and
|
CFP
Pointers
Contact Information |
8:30-8:50 - Welcome, Opening Remarks, Introduction
8:50 - 9:20 - Invited Talk I
9:20 - 9:50 - Invited Talk II
9:50 - 10:00 - discussion
10.00-10:30 coffee break
10:30-10:50
10:50-11:10
11:10-11:30
11:30-12:15 Poster Highlights (2 minutes each)
POSTER PAPERS:
A System for Feature Discovery and Selection in Probabilistic Relational Models
A Comparison of Inference Techniques for Semi-supervised Clustering with Hidden Markov
Random Fields
Using neural networks for relational learning
Learning Spatial Configuration Models Using Modified Dirichlet Priors
Relational Markov Networks for Collective Information Extraction
Clustering in Relational Biological Data
Relational Decision Networks
Hierarchical Probabilistic Relational Models for Collaborative Filtering
Cluster-based Concept Invention for Statistical Relational Learning
Learning Complex Motion Structures
A Dyanmic Programming Approach to Parameter Learning of Generative Models with Failure
Using Random Forests for Relational Learning
A Regularization Framework for Learning from Relational Data
Web Page Organization and Visualization Using Generative Topographic Mapping - A Pilot
Study
Playing Multiple Roles: Discovering Overlapping Roles in Social Networks
12:15 - 2:30 - Poster session/ Lunch
2:30-3:00 - Invited Talk III
3:00-3:30 - Invited Talk IV
3.30 - 4:00 coffee
4:00 - 4:30 - Invited Talk V
4:30-5.30 - Discussion and Wrap Up
|