| ID | Title | Primary Contact Author |
|---|
| 2 | A New Kernel for Classification of Networked Entities | Zhang, Dell |
| 6 | Efficient Discriminative Training Method for Structured Predictions | Yu, Huizhen |
| 7 | Representative Subgraph Sampling using Markov Chain Monte Carlo Methods | Borgwardt, Karsten |
| 9 | Combining near-optimal feature selection with gSpan | Borgwardt, Karsten |
| 10 | Infinite mixtures for multi-relational categorical data | Sinkkonen, Janne |
| 11 | Parameter Learning in Probabilistic Databases: A Least Squares Approach | Gutmann, Bernd |
| 13 | Structure and tie strengths in a mobile communication network | Saramäki, Jari |
| 18 | Induction of Node Label Controlled Graph Grammar Rules | Blockeel, Hendrik |
| 19 | Classification in Graphs using Discriminative Random Walks | Françoisse, Kevin |
| 20 | Min, Max and PTIME Anti-Monotonic Overlap Graph Measures | Van Dyck, Dries |
| 21 | Improved Software Fault Detection with Graph Mining | Eichinger, Frank |
| 23 | Markov Logic Improves Protein β-Partners Prediction | Frasconi, Paolo |
| 28 | Comparing Diffusion Models for Graph--Based Semi--Supervised Learning | Galstyan, Aram |
| 31 | A Hilbert-Schmidt Dependence Maximization Approach to Unsupervised Structure Discovery | Blaschko, Matthew |
| 43 | Inferring the structure and scale of modular networks | Hofman, Jake |
| 44 | An Online Algorithm for Learning a Labeling of a Graph | Pelckmans , Kristiaan |
| ID | Title | Primary Contact Author |
|---|
| 3 | Mining Common Semantic Patterns from Descriptions of Failure Knowledge | Kraines, Steven |
| 4 | A graph-theoretic approach for reducing one-versus-one multi-class classification to ranking | Waegeman, Willem |
| 5 | The skew spectrum of graphs | Kondor, Risi |
| 8 | Probabilistic models for the dynamics of tree-structured data | Dalvi, Nilesh |
| 12 | Randomization Techniques for Statistical Significance Testing on Graphs | Hanhijärvi, Sami |
| 15 | The All-Paths Covariance: a new covariance measure between nodes of a weighted, directed, graph | Mantrach, Amin |
| 17 | Scalable Algorithms for Structured Output Prediction | Vembu, Shankar |
| 24 | Mining music graphs through immanantal polynomials | Pinto, Alberto |
| 27 | CPT-L: an Efficient Model for Relational Stochastic Processes | Thon, Ingo |
| 32 | Mining graphs to discover new theorems in mathematics | Desrosiers, Christian |
| 33 | Graph Theoretic Measures for Identifying Affective Blockers of Spreading Processes in Dynamic Networks | Habiba, Habiba |
| 34 | A Structured-Outputs Method for Prediction of Protein Function | Sokolov, Artem |
| 37 | Prediction of Molecular Substructures from Mass Spectrograms Using Constraint Based Clustering | Drouillon, Pieter-Jan |
| 38 | A Method to extend Existing Document Clustering Procedures in order to include Relational Information | Witsenburg, Tijn |
| 39 | High-Order Regularization on Graphs | Zhou, Dengyong |
| 41 | A structured outputs method for predicting protein binding sites | Hamilton, Michael |
| 42 | Combining Optimal and Atomic Decomposition of Terminology Association Graphs | Meurs, Marie-Jean |
