A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split (1996)

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by Michael Kearns
Venue:Neural Computation
Citations:23 - 0 self

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101 An experimental and theoretical comparison of model selection methods. Machine Learning 27 – Michael Kearns, Yishay Mansour Y, Andrew Y. Ng, Dana Ron Z - 1997
10 Towards Robust Model Selection using Estimation and Approximation Error Bounds – Joel Ratsaby, Ronny Meir, Vitaly Maiorov - 1996
12 The Informational Complexity of Learning from Examples – Partha Niyogi - 1996
76 Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation – Michael Kearns, Dana Ron - 1997
2 Knowledge acquisition in statistical learning theory – Shai Fine - 1999
29 Preventing "Overfitting" of Cross-Validation Data – Andrew Y. Ng - 1997
2 Finite Sample Size Results for Robust Model Selection; Application to Neural Networks – Joel Ratsaby, Ronny Meir - 1995
2 Faithful Representations and Moments of Satisfaction: Probabilistic Methods in Learning and Logic – Lidror Troyansky, Prof Naftali Tishby - 1998
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization – Michael Kearns Att, Michael Kearns, Yishay Mansour - 1998
34 Adaptive model selection using empirical complexities – Gabor Lugosi, Andrew B. Nobel - 1999
59 Model Selection and Error Estimation – Peter L. Bartlett, Stephane Boucheron , Gabor Lugosi - 2001
3 Estimating the Expected Error of Empirical Minimizers for Model Selection – Tobias Scheffer, Thorsten Joachims - 1998
3 Error Estimation and Model Selection – Tobias Scheffer, Vom Fachbereich Informatik, Doktor Der Naturwissenschaften, Vorsitzender Prof, Dr. Stefan Jahnichen, Berichter Prof, Dr. Fritz Wysotzki - 1999
42 On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions – Partha Niyogi, Federico Girosi - 1996
26 Nonparametric time series prediction through adaptive model selection – Ron Meir, Lisa Hellerstein - 2000
12 Learning by Canonical Smooth Estimation, Part II: Learning and Choice of Model Complexity – Kevin L. Buescher, P. R. Kumar
4 A Scaling Law for the Validation-Set Training-Set Size Ratio – Isabelle Guyon - 1997
61 PAC-Bayesian Model Averaging – David A. McAllester - 1999
9 Annealed Theories of Learning – H. S. Seung - 1995