Selected Publications of Tom Bylander

S. O'Hara and T. Bylander, "Web Searching with Multiple Correct Answers", In Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics, pp. 45:1-45:6, 2014.

S. O'Hara and T. Bylander, "Predicting Website Correctness from Consensus Analysis", In Proceedings of the 2012 ACM Research in Applied Computation Symposium, pp. 49-54, 2012.

T. Bylander, "Learning Linear Functions with Quadratic and Linear Multiplicative Updates", In Proceedings of the 28th International Conference on Machine Learning, pp. 505-512, 2011.

S. O'Hara and T. Bylander, "Numeric Query Answering on the Web", International Journal on Semantic Web and Information Systems 7:1-17, 2011.

T. Bylander, "Transforming Examples for Multiclass Boosting", Journal of Experimental & Theoretical Artificial Intelligence 22:53-65, 2010.

R. Schwaerzel and T. Bylander, "Predicting Financial Time Series by Genetic Programming with Trigonometric Functions and High-Order Statistics", available from CiteSeer, 2006.

T. Bylander and L. Tate, "Using Validation Sets to Avoid Overfitting in AdaBoost", Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, pp. 544-549, 2006.

R. Schwaerzel and T. Bylander, "Predicting Currency Exchange Rates by Genetic Programming with Trigonometric Functions and High-Order Statistics", In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 955-956, 2006.

T. Bylander, "Estimating Generalization Error in Two-Class Datasets Using Out-of-Bag Estimates", Machine Learning 48:287-297, 2002.

T. Bylander, "A worst-case analysis of the perceptron and exponentiated update algorithms", Artificial Intelligence 106:335-352, 1998.

T. Bylander, "Learning Noisy Linear Threshold Functions", Technical Report, 1998.

T. Bylander, "The Binary Exponentiated Gradient Algorithm for Learning Linear Functions," Proceedings of the Tenth Annual Conference on Computational Learning Theory, pp. 184-192, 1997.

T. Bylander, "A Linear Programming Heuristic for Optimal Planning," Proceedings of the Fourteenth National Conference on Artificial Intelligence, pp. 694-699, 1997.

T. Bylander, "Worst-Case Absolute Loss Bounds for Linear Learning Algorithms," Proceedings of the Fourteenth National Conference on Artificial Intelligence, pp. 485-490, 1997.

T. Bylander and B. Rosen, "A Perceptron-like Online Algorithm for Tracking the Median," Proceedings of the IEEE International Conference on Neural Networks, pp. 2219-2224, 1997.

T. Bylander, "A Probabilistic Analysis of Propositional STRIPS Planning," Artificial Intelligence, 81:241-271, 1996.

T. Bylander, "Learning Linear Threshold Approximations Using Perceptrons," Neural Computation, 7:370-379, 1995.

T. Bylander, "The Computational Complexity of Propositional STRIPS Planning," Artificial Intelligence, 69:165-204, 1994.

T. Bylander, M. Weintraub, and S. R. Simon, "QUAWDS: Diagnosis using Different Models for Different Subtasks," In Second Generation Expert Systems, eds. J.-M. David, J.-P. Krivine, and R. Simmons, Springer-Verlag, Berlin, pp. 110-130, 1993.

T. Bylander, "Complexity results for serial decomposability," In Proceedings of the Tenth National Conference on Artificial Intelligence, San Jose, California, pp. 729-734, 1992.

T. Bylander, D. Allemang, M. C. Tanner, and J. R. Josephson, "The Computational Complexity of Abduction," Artificial Intelligence, 49:25-60, 1991. Also in Abductive Inference: Computation, Philosophy, Technology, eds. J. R. Josephson and S. G. Josephson, Cambridge University Press, Cambridge, UK, 1994.


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