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ORCIDMachine Learning, Volume 29, 1997
Volume 29, Number 1, October 1997
- Paul E. Utgoff, Neil C. Berkman, Jeffery A. Clouse:
Decision Tree Induction Based on Efficient Tree Restructuring. 5-44 - Shai Ben-David, Eyal Kushilevitz, Yishay Mansour:
Online Learning versus Offline Learning. 45-63 - Kenneth Basye, Thomas L. Dean, Jeffrey Scott Vitter
:
Coping with Uncertainty in Map Learning. 65-88
Volume 29, Numbers 2-3, November 1997
- Pat Langley, Gregory M. Provan, Padhraic Smyth:
Learning with Probabilistic Representations. 91-101 - Pedro M. Domingos, Michael J. Pazzani:
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss. 103-130 - Nir Friedman, Dan Geiger, Moisés Goldszmidt:
Bayesian Network Classifiers. 131-163 - Sanjoy Dasgupta:
The Sample Complexity of Learning Fixed-Structure Bayesian Networks. 165-180 - David Maxwell Chickering, David Heckerman:
Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables. 181-212 - John Binder, Daphne Koller, Stuart Russell, Keiji Kanazawa:
Adaptive Probabilistic Networks with Hidden Variables. 213-244 - Zoubin Ghahramani, Michael I. Jordan:
Factorial Hidden Markov Models. 245-273 - Naoki Abe, Hiroshi Mamitsuka:
Predicting Protein Secondary Structure Using Stochastic Tree Grammars. 275-301
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