Computational Learning Laboratory
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Research in the Computational Learning Laboratory

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Recent Papers

Langley, P., & Rogers, S. (in press). Cumulative learning of hierarchical skills. Proceedings of the Third International Conference on Development and Learning. San Diego, CA: IEEE Press.

Bay, S., Chrisman, L., Pohorille, A., & Shrager, J. (in press). Temporal aggregation bias and inference of causal regulatory networks. Journal of Computational Biology.

Langley, P., Shrager, J., Asgharbeygi, N., Bay, S., & Pohorille, A. (2004). Inducing explanatory process models from biological time series. Proceedings of the Ninth Workshop on Intelligent Data Analysis and Data Mining (pp. 85-90). Stanford, CA.

Choi, D., Kaufman, M., Langley, P., Nejati, N., & Shapiro, D. (2004). An architecture for persistent reactive behavior. Proceedings of the Third International Joint Conference on Autonomous Agents and Multi Agent Systems (pp. 988-995). New York: ACM Press.

Langley, P. (2004). Heuristics for scientific discovery: The legacy of Herbert Simon. In M. E. Augier & J. G. March (Eds.), Models of a Man: Essays in Memory of Herbert A. Simon. Cambridge, MA: MIT Press.

Thompson, C. A., Göker, M., & Langley, P. (2004). A personalized system for conversational recommendations. Journal of Artificial Intelligence Research, 21, 393-428.

Schroedl, S., Wagstaff, K., Rogers, S., Langley, P., & Wilson, C. (2004). Mining GPS traces for map refinement. Knowledge Discovery and Data Mining, 9, 59-87.

Sanchez, J. N., & Langley, P. (2003). An interactive environment for scientific model construction. Proceedings of the Second International Conference on Knowledge Capture (pp. 138-145). Sanibel Island, FL: ACM Press.

Bay, S. D., & Schwabacher, M. (2003). Mining distance-based outliers in near linear time with randomization and a simple pruning rule. Proceedings of The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Maloof, M. A., Langley, P., Binford, T. O., Nevatia, R., & Sage, S. (2003). Improved rooftop detection in aerial images with machine learning. Machine Learning, 53, 157-191.

Langley, P., George, D., Bay, S., & Saito, K. (2003). Robust induction of process models from time-series data. Proceedings of the Twentieth International Conference on Machine Learning (pp. 432-439). Washington, D.C.: AAAI Press.

Bay, S. D., Shrager, J., Pohorille, A., & Langley, P. (2003). Revising regulatory networks: From expression data to linear causal models. Journal of Biomedical Informatics, 35, 289-297.

Todorovski, L., Dzeroski, S., Langley, P., & Potter, C. (2003). Using equation discovery to revise an Earth ecosystem model of carbon net production. Ecological Modelling, 170, 141-154.

Yoo, J., Gervasio, M., & Langley, P. (2003). An adaptive stock tracker for personalized trading advice. Proceedings of the International Conference on Intelligent User Interfaces (pp. 197-203). Miami, Florida.