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Home / Proceedings / Papers from the 2015 AAAI Spring Symposium /

No. 3: Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches

All Papers

  • CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot

    Shiqi Zhang, Peter Stone

    PDF
  • Towards High-Level Probabilistic Reasoning with Lifted Inference

    Guy Van den Broeck

    PDF
  • Commonsense Reasoning Based on Betweenness and Direction in Distributional Models

    Steven Schockaert, Joaquín Derrac

    PDF
  • Dimensionality Reduction via Program Induction

    Kevin Ellis, Eyal Dechter, Joshua B. Tenenbaum

    PDF
  • Learning Probabilistic Logic Models with Human Advice

    Phillip Odom, Tushar Khot, Sriraam Natarajan

    PDF
  • FoxPSL: An Extended and Scalable PSL Implementation

    Sara Magliacane, Philip Stutz, Paul Groth, Abraham Bernstein

    PDF
  • Towards Learning a Knowledge Base of Actions from Experiential Microblogs

    Emre Kiciman

    PDF
  • A Unified Semantic Embedding: Relating Taxonomies and Attributes

    Sung Ju Hwang, Leonid Sigal

    PDF
  • Probabilistic Region Connection Calculus

    Codruta Liliana Girlea, Eyal Amir

    PDF
  • Combining Vector Space Embeddings with Symbolic Logical Inference over Open-Domain Text

    Matt Gardner, Partha Talukdar, Tom Mitchell

    PDF
  • Distributional-Relational Models: Scalable Semantics for Databases

    Andre Freitas, Siegfried Handschuh, Edward Curry

    PDF
  • Neural Relational Learning Through Semi-Propositionalization of Bottom Clauses

    Manoel Vitor Macedo Franca, Gerson Zaverucha, Artur S. d'Avila Garcez

    PDF
  • Distributional Semantic Features as Semantic Primitives — Or Not

    Gemma Boleda, Katrin Erk

    PDF
  • Latent Predicate Networks: Concept Learning with Probabilistic Context-Sensitive Grammars

    Eyal Dechter, Joshua Rule, Joshua B. Tenenbaum

    PDF
  • Enriching Word Embeddings Using Knowledge Graph for Semantic Tagging in Conversational Dialog Systems

    Asli Celikyilmaz, Dilek Hakkani-Tur, Panupong Pasupat, Ruhi Sarikaya

    PDF
  • Towards Extracting Faithful and Descriptive Representations of Latent Variable Models

    Vicente Iván Sánchez Carmona, Tim Rocktäschel, Sebastian Riedel, Sameer Singh

    PDF
  • Compositional Vector Space Models for Knowledge Base Inference

    Arvind Neelakantan, Benjamin Roth, Andrew McCallum

    PDF
  • Towards Ontologies in Variation

    Torsten Hahmann, Sheila A. McIlraith

    PDF
  • Towards A Model Theory for Distributed Representations

    Ramanathan Guha

    PDF
  • Neural-Symbolic Learning and Reasoning: Contributions and Challenges

    Artur d'Avila Garcez, Tarek R. Besold, Luc de Raedt, Peter Földiak, Pascal Hitzler, Thomas Icard, Kai-Uwe Kühnberger, Luis C. Lamb, Risto Miikkulainen, Daniel L. Silver

    PDF
  • Probability Distributions over Structured Spaces

    Arthur Choi, Guy Van den Broeck, Adnan Darwiche

    PDF
  • Learning Distributed Word Representations for Natural Logic Reasoning

    Samuel R. Bowman, Christopher Potts, Christopher D. Manning

    PDF
  • On Approximate Reasoning Capabilities of Low-Rank Vector Spaces

    Guillaume Bouchard, Sameer Singh, Théo Trouillon

    PDF

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