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9:00	Welcome and Introduction
9:05 - 10:45	Session 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 - 3:45	Session 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