SRL2004: Statistical Relational Learning and
its Connections to Other Fields
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- Feature Definition and Discovery 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 C. Bunescu and Raymond J. Mooney
- Clustering in Relational Biological Data, Aynur Dayanik and Craig G. Nevill-Manning
- Markov Logic: A Unifying Framework for Statistical Relational Learning, Pedro Domingos and Matthew Richardson
- Probabilistic Entity-Relationship Models, PRMs, and Plate Models, David Heckerman, Christopher Meek and Daphne Koller
- Relational Decision Networks, William H, Hsu and Roby Joehanes
- BLOG: Relational Modeling with Unknown Objects, Brian Milch, Bhaskara Marthi and Stuart Russell
- Autocorrelation and Relational Learning: Challenges and Opportunities, Jennifer Nevillle, Ozgur Simsek and David Jensen
- Hierarchical Probabilistic Relational Models for Collaborative Filtering, Jack Newton and Russell Greiner
- Learning Complex Motion Structures, Fabio Tozento Ramos and Hugh F. Durrant-Whyte
- A Dynamic Programming Approach to Parameter Learning of Generative Models with Failure, Taisuke Sato and Yoshitaka Kameya
- Cluster-based Concept Invention for Statistical Relational Learning, Alexandrin Popescul and Lyle H. Ungar
- A Random Forest Approach to Relational Learning, Anneleen Van Assche, Celine Vens, Hendrik Blockeel and Saso Dzeroski
- Playing Multiple Roles: Discovering Overlapping Roles in Social Networks, Alicia P. Wolfe and David Jensen
- Web Page Organization and Visualization Using Generative Topographic Mapping A Pilot Study, Xiao-Feng Zhang, Chak-Man Lam and William K. Cheung
- A Regularization Framework for Learning from Graph Data, Dengyong Zhou and Bernhard Scholkopf