Recent Publications

• Gautam Kunapuli, Rich Maclin & Jude Shavlik (2011). 
  Advice Refinement for Knowledge-Based Support Vector Machines. Proceedings of the Twenty-Fifth Conference on Neural Information Processing Systems (NIPS 2011).
• G. Kunapuli, R. Maclin & J. Shavlik (2011). 
  Advice Refinement for Knowledge-Based Support Vector Machines. Workshop on Combining Learning Strategies for Reducing Label Cost at ICML 2011. 
• Gautam Kunapuli, Kristin P. Bennett, Rich Maclin & Jude Shavlik (2010). 
  The Adviceptron: Giving Advice To The Perceptron. Proceedings of the Conference on Artificial Neural Networks In Engineering (ANNIE 2010), St. Louis, MO. 
  
• Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page & Jude Shavlik (2010). 
  Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. Proceedings of the 20th International Conference on Inductive Logic Programming, Florence, Italy. 
• G. Kunapuli, K.P. Bennett, A. Shabbeer, R. Maclin & J. Shavlik (2010).
  Online Knowledge-Based Support Vector Machines. Proceedings of the European Conference on Machine Learning (ECML 2010), Barcelona, Spain.
• S. Natarajan, G. Kunauli, R. Maclin, D. Page, C. O'Reilly, T. Walker & J. Shavlik (2010).  
  Learning from Human Teachers: Issues and Challenges in Bootstrap Learning. AAMAS 2010 Workshop on Agents Learning Interactively from Human Teachers, Toronto, Canada. 
• L. Torrey, J. Shavlik, T. Walker & R. Maclin (2009).
  Transfer Learning via Advice Taking. In J. Koronacki, S. Wirzchon, Z. Ras & J. Kacprzyk, editors, Recent Advances in Machine Learning, dedicated to the memory of Ryszard S. Michalski. Springer Studies in Computational Intelligence.
• S. Natarajan, G. Kunapuli, C. O'Reilly, R.Maclin, T. Walker, D. Page & J.Shavlik (2009). 
  ILP for Bootstrapped Learning: A Layered Approach to Automating the ILP Setup Problem. Presented at the Nineteenth Conference on Inductive Logic Programming, Leuven, Belgium. 
• L. Torrey, J. Shavlik, T. Walker & R. Maclin (2008). 
  Rule Extraction for Transfer Learning. In J. Diederich, editor, Rule Extraction from Support Vector Machines, pp. 67-82. Springer. 
• L. Torrey, T. Walker, R. Maclin & J. Shavlik (2008). 
  Advice Taking and Transfer Learning: Naturally Inspired Extensions to Reinforcement Learning. AAAI Fall Symposium on Naturally Inspired AI, Washington, DC. 
• R. Maclin, E. Wild, J. Shavlik, L. Torrey and T. Walker (2007).
  Refining Rules Incorporated into Knowledge-Based Support Vector Learners Via Successive Linear Programming (PDF) . Proceedings of the Twenty Second National Conference on Artificial Intelligence (AAAI'07), Vancouver, BC.
• L. Torrey, J. Shavlik, T. Walker and R. Maclin (2007).
  Relational Macros for Transfer in Reinforcement Learning. (PDF) . Proceedings of the Seventeenth Conference on Inductive Logic Programming (ILP'07), Corvallis, Oregon.
• T. Walker, L. Torrey, J. Shavlik, and R. Maclin (2007).
  Building Relational World Models for Reinforcement Learning. (PDF) . Proceedings of the Seventeenth Conference on Inductive Logic Programming (ILP'07), Corvallis, Oregon.
• R. Maclin, J. Shavlik, T. Walker and L. Torrey (2006).
  A Simple and Effective Method for Incorporating Advice into Kernel Methods (PDF) . Proceedings of the Twenty First National Conference on Artificial Intelligence (AAAI'06), Boston, MA.
• L. Torrey, J. Shavlik, T. Walker and R. Maclin (2006).
  Skill Acquisition via Transfer Learning and Advice Taking. (PDF) . Proceedings of the Seventeenth European Conference on Machine Learning (ECML'06), Berlin, Germany.
• R. Maclin, J. Shavlik, L. Torrey, T. Walker and E. Wild (2005).
  Giving Advice about Preferred Actions to Reinforcement Learners Via Knowledge-Based Kernel Regression (PDF) . Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI'05), Pittsburgh, PA.
• R. Maclin, J. Shavlik, L. Torrey and T. Walker (2005).
  Knowledge Based Support Vector Regression for Reinforcement Learning (PDF) . IJCAI'05 Workshop on Reasoning, Representation, and Learning in Computer Games, Edinburgh, Scotland.
• L. Torrey, T. Walker, J. Shavlik and R. Maclin (2005).
  Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another. (PDF) . Proceedings of the Sixteenth European Conference on Machine Learning (ECML'05), Porto, Portugal.
• L. Torrey, T. Walker, J. Shavlik and R. Maclin (2005).
  Knowledge Transfer Via Advice Taking (PDF) . Proceedings of the Third International Conference on Knowledge Capture (KCAP'05), Banff, Canada. Poster (PDF). Abstract.
• M. Joshi, T. Pedersen and R. Maclin (2005).
  A Comparative study of support vector machines applied to the supervised word sense disambiguation problem in the medical domain (PDF) . Proceedings of the 2nd Indian International conference on Artificial Intelligence (IICAI-05), Pune, India.
• T. Walker, J. Shavlik and R. Maclin (2004).
  Relational Reinforcement Learning via Sampling the Space of First-Order Conjunctive Features (PDF) . Proceedings of the ICML Workshop on Relational Reinforcement Learning, Banff, Canada.
• Bennett, K., Demiriz, A. and Maclin, R. (2002).
  Exploiting Unlabeled Data in Ensemble Methods (PDF) Proceedings of the Eighth ACM SIGKDD Internation Conference on Knowledge Discovery and Data Mining, Edmonton, Alberta, Canada.
• Opitz, D. and Maclin, R. (1999).
  Popular ensemble methods: An empirical study (PDF)   (Postscript) . Journal of AI Research, 11, 169-198.
• Maclin, R. (1998).
  Boosting classifiers regionally. (PDF)   (Postscript) . Proceedings of the Fifteenth National Conference on Artificial Intelligence, pp. 700-705, Madison, WI.
• Maclin, R. and Shavlik, J. W. (1998).
  Creating advice-taking reinforcement learners. (PDF)   (Postscript) . in S. Thrun and L. Pratt (eds) Learning to Learn, Kluwer Academic.
• Maclin, R. and Opitz, D. (1997).
  An empirical comparison of bagging and boosting. (PDF)   (Postscript) . Proceedings of the Fourteenth National Conference on Artificial Intelligence, Providence, RI.
• Asker, L. and Maclin, R. (1997).
  Feature engineering and classifer selection: A case study in Venusian volcano detection. (PDF)   (Postscript) . Proceedings of the Fourteenth International Conference on Machine Learning, Nashville, TN.
• Asker, L. and Maclin, R. (1997).
  Ensembles as a sequence of classifiers. (PDF)   (Postscript) . Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan.
• Maclin, R. and Shavlik, J. W. (1996).
  Creating advice-taking reinforcement learners. (PDF)   (Postscript) . Machine Learning, 22, 251-281.
• Maclin, R. and Shavlik, J. W. (1995).
  Combining the predictions of multiple classifiers: Using competitive learning to initialize neural networks. (PDF)   (Postscript) . Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada.
• Maclin, R. (1995).
  Learning from Instruction and Experience: Methods for Incorporating Procedural Domain Theories into Knowledge-Based Neural Networks. Ph.D. Thesis, Department of Computer Sciences, University of Wisconsin-Madison. (Also appears as UW Technical Report CS-TR-95-1285)
  First half (Postscript)
  First half (PDF)
  Second half (Postscript)
  Second half (PDF)
• Maclin, R. and Shavlik, J. W. (1994).
  Incorporating Advice into Agents that Learn from Reinforcements. (PDF)   (Postscript) . Proceedings of the Twelfth National Conference on Artificial Intelligence, pp. 694-699, Seattle, WA. (A longer version appears as UW-CS TR 1227 (PDF)   (Postscript) .)
• Maclin, R. and Shavlik, J. W. (1993).
  Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein Folding. (PDF)   (Postscript) . Machine Learning, 11 (2/3), pp. 195-215. Other versions of this paper appear in the Proceedings of the Tenth National Conference on Artificial Intelligence, 1992, pp. 165-170, and in Hanson, S., Drastal, G. and Rivest, R., eds., Computational Learning Theory and Natural Learning Systems, 1994, MIT Press.
• Maclin, R. and Shavlik, J. W. (1991).
  Refining Domain Theories Expressed as Finite-State Automata. (PDF)   (Postscript) . Machine Learning: Proceedings of the Eighth International Conference , pp. 524-528, Chicago, IL.
• Stewart, J. and Maclin, R. (1990).
  Representing Genotype-to-Phenotype Mappings. Journal of Biological Education, 24 (2), pp. 113-116.
• Maclin, R. and Shavlik, J. W. (1989).
  Enriching Vocabularies Using Explanation-Based Learning. Machine Learning: Proceedings of the Sixth International Conference , pp. 444-446, Ithaca, NY.
• Koedinger, K., Maclin, R., Streibel, M. and Stewart, J. (1987).
  Intelligent Tutoring Systems Design Issues for a Genetics Laboratory Called MENDEL. Proceedings of the Third International Conference on Artificial Intelligence and Education , Pittsburgh, PA.