Statistical Inference





Rajnarayan, D., and Wolpert, D. H. "Bias-Variance trade-offs: Novel Applications", invited contribution to Encyclopedia of Machine Learning, in press.

Wolpert, D.H., “Supervised Learning Theory,” invited contribution to Encyclopedia of Cognitive Science, Robert French et al. (Ed.'s), 2001, in press. PDF or Postscript .



Wolpert, D.H. “The Supervised Learning No-Free-Lunch Theorems,” invited contribution to World conference on Soft Computing 2001, in press. PDF or Postscript.



Smyth, P. and Wolpert, D. H., “Linearly Combining Density Estimators via Stacking”, Machine Learning Journal, 36, 59-83, 1999. PDF or Postscript.



Wolpert, D.H., and Macready, W.G., “An Efficient Method to Estimate Bagging’s Generalization Error”, Machine Learning Journal, 35, 41-55, 1999. PDF or Postscript.



Smyth, P. and Wolpert, D. H., “Stacked Density Estimation”, Neural Information Processing Systems 10, MIT Press, 1998. PDF or Postscript.



Wolpert, D.H., Knill, E., and Grossman, T., “Some results concerning off-training-set and IID error for the Gibbs and Bayes optimal generalizers”, Statistics and Computing, 8(1), March 1998, pp. 35--54. PDF or Postscript.



Delwart, E.L., Pan, H., Sheppard, H.W., Wolpert, D.H.,Neumann, A.U., Korber, B.T., Mullins, J.I., “Slower Evolution of HIV-1 quasispecies evolution during progression to AIDS”, J. Virol, October, 71(10), 7498-7508, 1997. PDF or Postscript.



Smyth, P. and Wolpert, D. H., “Anytime Exploratory Data Analysis for Massive Data Sets”, The Third International Conference on Knowledge Discovery and Data Mining, AAAI Press, 1997. PDF or Postscript.



Wolpert, D.H., “On Bias plus Variance”, Neural Computation, 9, 1997. PDF or Postscript.



Wolpert, D.H., “The Lack of A Priori Distinctions between Learning Algorithms”, Neural Computation, 8, 1341 - 1390, 1996. PDF or Postscript.



Wolpert, D.H., “The Existence of A Priori Distinctions between Learning Algorithms”, Neural Computation, 8, 1996. PDF or Postscript.



Wolpert, D.H., “Determining Whether Two Data Sets are from the Same Distribution”, in Maximum Entropy and Bayesian Methods 1995, Ed. K. Hanson and R. Silver, Kluwer Academic press, 1996. PDF or Postscript.



Wolpert, D.H., “The Bootstrap is Inconsistent with Probability Theory”, in Maximum Entropy and Bayesian Methods 1995, Ed. K. Hanson and R. Silver, Kluwer Academic press, 1996. PDF or Postscript.



Wolpert, D.H., Strauss, C.E., “What Bayes has to say about the evidence procedure”, in Maximum Entropy and Bayesian Methods 1993, Ed. G. Heidbreder, Kluwer Academic press, 1996. PDF or Postscript.



Wolpert, D.H., “Reconciling Bayesian and non-Bayesian analysis”, in Maximum Entropy and Bayesian Methods 1993, Ed. G. Heidbreder, Kluwer Academic press, 1996. PDF or Postscript.



Kohavi, R., and Wolpert, D.H., “Bias Plus Variance Decomposition for Zero-One Loss Functions”, Proceedings of the International Machine Learning Conference 13, Ed. Lorenza and Saiita, Morgan Kauffman,1996. PDF or Postscript.



Wolpert, D.H., and Wolf, D.R., “Estimating Functions of Probability Distributions from a Finite Set of Samples”, Physical Review E, 52, p. 6841, 1995. PDF or Postscript.



Wolpert, D.H., “Horizontal Generalization”, in Proceedings of the International Machine Learning Conference 12, Ed. A. Prieditis and S. Russell, Morgan Kauffman, 1995. PDF or Postscript.



Wolpert, D.H., “On the Bayesian 'Occam Factors' Argument for Occam's Razor”, in Computational Learning Theory and Natural Learning Systems III, Ed. T. Petsche et al., MIT Press, 1995. PDF or Postscript.



Wolpert, D.H., “The Relationship Between the Various Supervised Learning Formalisms”, in The Mathematics of Generalization, Ed. D. Wolpert, Addison-Wesley, 1994. PDF or Postscript.



Wolpert, D.H., and Lapedes, A.S., “A Rigorous Investigation of Exhaustive Learning”, in The Mathematics of Generalization, Ed. D. Wolpert, Addison-Wesley, 1994. PDF or Postscript.



Wolpert, D.H., “Filter Likelihoods and Exhaustive Learning”, in Computational Learning Theory and Natural Learning Systems II, Ed. S. Hanson et al., MIT Press,1994. PDF or Postscript.



Wolpert, D.H., “Bayesian back-propagation over I-O functions rather than weights”, in Advances in Neural Information Processing Systems VI, Ed. S. Hanson et al., Morgan Kauffman, 1994. PDF or Postscript.



Strauss, C.E., Wolpert, D.H., Wolf, D.R., “Alpha, Evidence, and the Entropic Prior”, in Maximum Entropy and Bayesian Methods 1992, Ed. A. Mohammed-Djafari, Kluwer, 1994. PDF or Postscript.



Wolpert, D.H., “Combining Generalizers Using Partitions of the Learning Set”, in 1992 Lectures in Complex Systems, Ed. L. Nadel et al., Addison-Wesley, 1994. PDF or Postscript.



Wolpert, D.H., “On the Use of Evidence in Neural Networks”, in Advances in Neural Information Processing Systems V, Ed. S. Hanson et al., Morgan Kauffman, 1993. PDF or Postscript.



Korber, B.T., Farber, R.M., Wolpert, D.H., and Lapedes, A.S., “Covariation of Mutations in the V3 Loop of HIV-1: An Information-Theoretic Analysis”, Proceedings of the National Academy of Sciences, 90, 7176-7180, 1993. PDF or Postscript.



Wolpert, D.H., “How to Deal with Multiple Possible Generalizers”, in Fast Learning and Invariant Object Recognition, Ed. B. Soucek, Wiley and Sons, 1992. PDF or Postscript.



Wolpert, D.H., “Stacked Generalization”, Neural Networks, 5, 241-259, 1992. PDF or Postscript.



Wolpert, D.H., “On the Connection Between In-Sample Testing and Generalization Error”, Complex Systems, 6, 47-94, 1992. PDF or Postscript.



Wolpert, D.H., “The Relationship Between Occam's Razor and Convergent Guessing”, Complex Systems, 4, 319-368, 1990. PDF or Postscript.



Wolpert, D.H., “Using a Mathematical Theory of Generalization to Construct a Generalizer Superior to NETtalk”, Neural Networks, 3, 445-452, 1990. PDF or Postscript.



Wolpert, D.H., “A mathematical Theory of Generalization: part I, part II”, Complex Systems, 4,151-200, 201-249, 1990. PDF or Postscript.



Wolpert, D.H., “A benchmark for how well neural nets generalize”, Biological Cybernetics, 61 303-313, 1989. PDF or Postscript.