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» A probabilistic framework for relational clustering
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106
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ILP
2005
Springer
15 years 5 months ago
A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment
We propose a new approach to Inductive Logic Programming that systematically exploits caching and offers a number of advantages over current systems. It avoids redundant computati...
Héctor Corrada Bravo, David Page, Raghu Ram...
75
Voted
CLUSTER
2008
IEEE
15 years 6 months ago
Empirical-based probabilistic upper bounds for urgent computing applications
—Scientific simulation and modeling often aid in making critical decisions in such diverse fields as city planning, severe weather prediction and influenza modeling. In some o...
Nick Trebon, Peter H. Beckman
AAAI
2008
15 years 2 months ago
A General Method for Reducing the Complexity of Relational Inference and its Application to MCMC
Many real-world problems are characterized by complex relational structure, which can be succinctly represented in firstorder logic. However, many relational inference algorithms ...
Hoifung Poon, Pedro Domingos, Marc Sumner
71
Voted
KI
2009
Springer
15 years 6 months ago
Generalized Clustering via Kernel Embeddings
Abstract. We generalize traditional goals of clustering towards distinguishing components in a non-parametric mixture model. The clusters are not necessarily based on point locatio...
Stefanie Jegelka, Arthur Gretton, Bernhard Sch&oum...
ACSC
2005
IEEE
15 years 5 months ago
A Framework of Filtering, Clustering and Dynamic Layout Graphs for Visualization
Many classical graph visualization algorithms have already been developed over the past decades. However, these algorithms face difficulties in practice, such as the overlapping n...
Xiaodi Huang, Peter Eades, Wei Lai