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.