Bay, S., Saito, K., Ueda, N., Langley, P. A Framework for Discovering Anomalous Regimes in Multivariate Time-Series Data with Local Models. PDF.
Bay, S., Chrisman, L., Pohorille, A., and Shrager, J. (to appear). Temporal Aggregation Bias and Inference of Causal Regulatory Networks. Journal of Computational Biology
J. Shrager, R. Labiosa, JP Massar, M. Travers, S. Bay, J. Elhai, A. Pohorille, K. Arrigo, P. Langley, D. Bhaya, and A. Grossman. (2004) The BioLingua Multi-Cyanobacterial BioComputation Platform, and its Application in Cyclodynamic Microarray Analysis of Cyanobacterial Light Acclimation. Gordon Research Conference. Roscoff, France.
Shrager, J., Labiosa, R., Bay, S., Arrigo, K., Bhaya, D., Tu, C., Grossman, A. (2004). Genome-wide Analyses of Light Driven and Circadian Expression Response in Synechocystis PCC 6803. Proceedings of the 12th American Geophysical Union Ocean Sciences Meeting.
Bay, S. D., and 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. PDF. Postscript.
George, D., Saito, K., Langley, P., Bay, S., & Arrigo, K. (2003). Discovering ecosystem models from time-series data. Proceedings of the Sixth International Conference on Discovery Science. Postscript.
Saito, K., George, D., Bay, S., & Shrager, J. (2003). Inducing biological models from temporal gene expression data. Proceedings of the 6th International Conference on Discovery Systems. Sapporo, Japan.
Langley, P., George, D., and Bay, S. (2003). Robust Induction of Process Models from Time-Series Data. Proceedings of the Twentieth International Conference on Machine Learning. Postscript.
Bay, S. D., Chrisman, L., Pohorille, A., and Shrager, J. (2003). Temporal Aggregation Bias and Inference of Causal Regulatory Networks. IJCAI-2003 Workshop on Learning Graphical Models for Computational Genomics. Postscript. PDF.
Bay, S. D., Shrager, J., Pohorille, A., and Langley, P. (2002). Revising Regulatory Networks: From Expression Data to Linear Causal Models. Journal of Biomedical Informatics. Postscript. PDF.
Chrisman, L., Langley, P., Bay, S. D., and Pohorille, A. (2003). Incorporating biological knowledge into evaluation of causal regulatory hypotheses. Proceedings of the Pacific Symposium on Biocomputing. Postscript.
Saito, K., Bay, S. D., and Langley, P. (2002). Revising Qualitative Models of Gene Regulation. Proceedings of the Fifth International Conference on Discovery Science. Lubeck, Germany. Postscript. PDF.
Bay, S. D., Shapiro, D. G., and Langley, P. (2002). Revising engineering models: Combining computational discovery with knowledge. Proceedings of the Thirteenth European Conference on Machine Learning. Helsinki, Finland. Postscript. PDF.
Bay, S. D. (2001). Clustering and Merging Geographic Regions Based on Sample Information. PAKDD workshop on Spatial and Temporal Data Mining. Hong Kong.
Bay, S. D. and Pazzani, M. J. (2001). Detecting Group Differences: Mining Contrast Sets. Data Mining and Knowledge Discovery. Postscript. PDF.
Bay, S. D. (2001). Multivariate Discretization for Set Mining. Knowledge and Information Systems. Postscript. PDF.
Bay, S. D., Kibler, D., Pazzani, M. J., and Smyth, P. (2001). The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation. Information Processing Society of Japan Magazine. Volume 42, Number 5, pages 462-466. English language version reprinted in SIGKDD Explorations. Volume 2, Issue 2, pages 81-85, 2000. Postscript. PDF.
Bay, S. D. (2000). Multivariate Discretization of Continuous Variables for Set Mining. Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Postscript. PDF.
Bay, S. D. and Pazzani, M. J. (2000). Discovering and Describing Category Differences: What makes a discovered difference insightful?. Proceedings of the Twenty Second Annual Meeting of the Cognitive Science Society. Postscript. PDF.
Bay, S. D. and Pazzani, M. J. (2000). Characterizing Model Errors and Differences. Proceedings of the Seventeenth International Conference on Machine Learning. Postscript. PDF. Slides.
Bay, S. D. and Pazzani, M. J. (2000). Characterizing Model Performance in the Feature Space. ICML 2000 Workshop on What Works Well Where?. Postscript. PDF.
Bay, S. D., Kibler, D., Pazzani, M. J., and Smyth, P. (2000). The UC Irvine Knowledge Discovery in Databases Archive. The 32nd Symposium on the Interface: Computing Science and Statistics. Invited poster.
Bay, S. D. and Pazzani, M. J. (1999). Detecting Change in Categorical Data: Mining Contrast Sets. Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Postscript. PDF.
Pazzani, M. J. and Bay, S. D. (1999). The Independent Sign Bias: Gaining Insight from Multiple Linear Regression. Proceedings of the Twenty-First Annual Meeting of the Cognitive Science Society. PDF. Postscript. Slides.
Bay, S. D. (1999). Nearest Neighbor Classification from Multiple Feature Subsets. Intelligent Data Analysis. 3(3):191-209. Postscript. PDF. (preprint).
Bay, S. D. (1998). Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets. Proceedings of the Fifteenth International Conference on Machine Learning. Madison, WI. Postscript. PDF.
Bay, S. D. (1997). Nearest Neighbour Classification from Multiple Data Representations. Master's thesis, University of Waterloo, Department of Systems Design Engineering.