William W. Cohen's Papers: Explanation-Based Learning

  1. William Yang Wang, Kathryn Mazaitis, and William W. Cohen (2015): A Soft Version of Predicate Invention Based on Structured Sparsity in IJCAI-2015.
  2. William Yang Wang, Kathryn Mazaitis, Ni Lao, Tom Mitchell, and William W. Cohen (2015): Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic in Machine Learning, 2015.
  3. William Yang Wang, Kathryn Mazaitis, William W. Cohen (2013): Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic in CIKM-2013 (Honorable Mention for Best Paper at CIKM-2013). (Originally published as: William Yang Wang, Kathryn Mazaitis, William W. Cohen (2013): Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic in arxiv 1305.2254; William Yang Wang, Kathryn Mazaitis, William W. Cohen (2013): Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic in ICML 2103 Workshop on Inferning).
  4. William W. Cohen, Russell Greiner, and Dale Schuurmans (1994): Probabilistic hill-climbing in Computational learning theory and natural learning systems (Volume II), MIT Press..
  5. William W. Cohen (1994): Incremental abductive EBL in Machine Learning 15(1): 5-24 (1994).
  6. William W. Cohen (1994): Grammatically biased learning: learning logic programs using an explicit antecedent description language in Artif. Intell. 68(2): 303-366 (1994).
  7. William W. Cohen (1992): Using distribution-free learning theory to analyze solution path caching mechanisms in Computational Intelligence 8: 336-375 (1992).
  8. William W. Cohen (1992): Desiderata for generalization-to-n algorithms in AII 1992: 140-150.
  9. William W. Cohen (1992): Compiling prior knowledge into an explicit bias in ICML 1992: 102-110.
  10. William W. Cohen (1992): Abductive explanation based learning: A solution to the multiple inconsistent explanation problem in Machine Learning 8: 167-219 (1992).
  11. William W. Cohen (1993): A Review of `Creating a Memory of Causal Relationships' by Michael Pazzani in Machine Learning (1993).
  12. William W. Cohen (1991): The generality of overgenerality in ICML 1991: 490-494.
  13. William W. Cohen (1990): Learning from textbook knowledge: A case study in AAAI 1990: 743-748.
  14. William W. Cohen (1990): Learning approximate control rules of high utility in ICML 1990: 268-276.
  15. William W. Cohen (1990): An analysis of representation shift in concept learning in ICML 1990: 104-112.
  16. William W. Cohen (1990): Learning from Examples and an "Abductive Theory" in Proc. of the 1990 AAAI Spring Symposium on Abduction.
  17. William W. Cohen (1988): Generalizing number and learning from multiple examples in explanation-based learning in ICML 1988: 256-269.
  18. William W. Cohen, Jack Mostow & Alex Borgida (1988): Generalizing number in explanation-based learning in Proc. of the 1988 AAAI Spring Symposium on Explanation-Based Learning.

[Selected papers| By topic: Deep Learning| Info Extraction/Reading| Topic Modeling| Learning in Graphs| Matching/Data Integration| Text Categorization| Rule Learning| Explanation-Based Learning| Formal Results| Inductive Logic Programming| Collaborative Filtering| Applications| Intelligent Tutoring| GNAT System| By year: All papers]