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SRL2006: Open Problems in Statistical Relational Learning

Schedule (Updated 6/28/06)

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All regular talks are 15 minutes long.

9:00 Welcome and Introduction
9:05 - 10:45Session 1: Inference
9:05 MPE and Partial Inversion in Lifted Probabilistic Variable Elimination
Presentation Slides (ppt)
Rodrigo de Salvo Braz, Eyal Amir, Dan Roth
9:20 Bias/Variance Analysis for Network Data
Presentation Slides (pdf)
Jennifer Neville, David Jensen
9:35 Invited Talk: Maximum Margin Structured Labeling: Optimization Algorithms, Generalization Bounds, and Consistency
Presentation Slides (pdf)
David McAllester
10:30 Discussion- Brian Milch
10:45 - 11:00 Coffee Break
11:00 - 12:15 Session 2: Inference continued, and Relational Reinforcement Learning
11:00 Tractable Learning and Inference with High-Order Representations
Presentation Slides (pdf)
Aron Culotta, Andrew McCallum
11:15 First Order Decision Diagram for Relational MDPs
Saket Joshi, Roni Khardon, Chenggang Wang
11:30 Online Feature Discovery in Relational Reinforcement Learning
Scott Sanner
11:45 Open Problem: Dynamic Relational Models for Improved Hazardous Weather Prediction
Presentation Slides (pdf)
Amy McGovern, Adrianna Kruger, Derek Rosendahl, Kelvin Droegemeier
11:55 Discussion - Alan Fern
12:15 - 2:00

Lunch and Poster Session

JOINT POSTER SESSION with Learning in Structured Output Spaces and Statistic Network Analysis Models, Issues and New Directions

NEW: List of Posters at the joint session (PDF)
Relational Clustering for Entity Resolution Queries
Poster Slides (ppt)
Indrajit Bhattacharya, Louis Licamele, Lise Getoor
Model-Assisted Approaches for Relational Reinforcement Learning: Some Challenges for the SRL Community
Poster Slides (pdf)
Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
Tractable Learning and Inference with High-Order Representations
Aron Culotta, Andrew McCallum
The Thing We Tried That Worked: Utile Distinctions for Relational Reinforcement Learning
Poster Slides (pdf)
Will Dabney, Amy McGovern
View Learning Extended: Inventing New Tables for Statistical Relational Learning
Jesse Davis, Elizabeth Burnside, David Page, Vítor Santos Costa
MPE and Partial Inversion in Lifted Probabilistic Variable Elimination
Rodrigo de Salvo Braz, Eyal Amir, Dan Roth
MAP Estimation in MRFs via Rank Aggregation
Poster Slides (ppt)
Rahul Gupta, Sunita Sarawagi
First Order Decision Diagram for Relational MDPs
Saket Joshi, Roni Khardon, Chenggang Wang
Learning Systems of Concepts with an Infinite Relational Model
Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griffiths, Takeshi Yamada, Naonori Ueda
(Also appearing at AAAI 2006)
A General Model for Relational Clustering
Poster Slides (ppt)
Bo Long, Zhongfei Zhang, Xiaoyun Wu, Philip Yu
Recursive Random Fields
Daniel Lowd, Pedro Domingos
Structure Refinement in First Order Conditional Influence Language
Poster Slides (ppt)
Sriraam Natarajan, Weng-Keen Wong, Prasad Tadepalli
Bias/Variance Analysis for Network Data
Jennifer Neville, David Jensen
Online Feature Discovery in Relational Reinforcement Learning
Scott Sanner
Empirical Comparison of Approximate Inference Algorithms for Networked Data
Poster Slides (pdf)
Prithviraj Sen, Lise Getoor
Learning Infinite Hidden Relational Models
Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel
Open Problems in Relational Data Clustering
Poster Slides (ppt)
Adam Anthony, Marie desJardins
Speaking of Relations: Connecting Statistical Relational Learning and Multi-Agent Systems
Marie desJardins, Matthew E. Gaston
Using Predictive Clustering and Probabilistic Constraint Solving for Structural Predictions
Poster Slides (pdf)
Kurt Driessens, Hendrik Blockeel
Expressivity Analysis for PL-Languages
Poster Slides (pdf)
Manfred Jaeger, Kristian Kersting, Luc De Raedt
Toward Statistical Predicate Invention
Poster Slides (pdf)
Stanley Kok, Pedro Domingos
Open Problem: Dynamic Relational Models for Improved Hazardous Weather Prediction
Amy McGovern, Adrianna Kruger, Derek Rosendahl, Kelvin Droegemeier

All accepted papers may be presented as posters. The poster session will be open to attendees of all the ICML workshops during this common lunch period.

2:00 - 3:00 Session 3: Structure Learning
2:00 View Learning Extended: Inventing New Tables for Statistical Relational Learning
Presentation Slides (ppt)
Jesse Davis, Elizabeth Burnside, David Page, Vítor Santos Costa
2:15 Structure Refinement in First Order Conditional Influence Language
Sriraam Natarajan, Weng-Keen Wong, Prasad Tadepalli
2:30 Recursive Random Fields
Presentation Slides (ppt)
Daniel Lowd, Pedro Domingos
2:45 Discussion - Lise Getoor
3:00 - 3:45Session 4: Predicate Invention
3:00 Learning Systems of Concepts with an Infinite Relational Model
Presentation Slides (pdf)
Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griffiths, Takeshi Yamada, Naonori Ueda
3:15 Learning Infinite Hidden Relational Models
Presentation Slides (ppt)
Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel
3:30 Discussion - Pedro Domingos
3:45 - 4:00 Coffee Break
4:00 - 5:30 Session 5: Applications and Systems
(Talks in this session are 10 minutes long)
4:00 Digital Libraries
Presentation Slides (ppt)
Andrew McCallum
4:10 Speaking of Relations: Connecting Statistical Relational Learning and Multi-Agent Systems
Marie desJardins, Matthew E. Gaston
4:20 SRL for Computer Vision
Presentation Slides (ppt)
Kevin Murphy
4:30 Discussion: Applications
4:45 Discussion: SRL Languages and Systems, Manfred Jaeger
5:00 Wrap-up
5:30 End of workshop