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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Wolf: An extended and scalable PSL implementation
Organization Unit
  • Sara Magliacane
  • Philip Stutz
  • Paul Groth
  • Abraham Bernstein
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Event Title AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches
Event Type conference
Event Location Stanford University, CA
Event Start Date March 23 - 2015
Event End Date March 25 - 2015
Series Name AAAI Spring Symposium
Place of Publication Palo Alto, California
Publisher AAAI Press
Abstract Text In this paper we present foxPSL, an extended and scalable implementation of Probabilistic Soft Logic (PSL) based on the distributed graph processing framework SIGNAL/COLLECT. PSL is a template language for hinge-loss Markov Random Fields, in which MAP inference is formulated as a constrained convex minimization problem. A key feature of PSL is the capability to represent soft truth values, allowing the expression of complex domain knowledge. To the best of our knowledge, foxPSL is the first end-to-end distributed PSL implementation, supporting the full PSL pipeline from problem definition to a distributed solver that implements the Alternating Direction Method of Multipliers (ADMM) consensus optimization. foxPSL provides a Domain Specific Language that extends standard PSL with a type system and existential quantifiers, allowing for efficient grounding. We compare the performance of foxPSL to a state-of-the-art implementation of ADMM consensus optimization in GraphLab, and show that foxPSL improves both inference time and solution quality.
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Other Identification Number merlin-id:11653
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