Reinforcement Learning: A Survey - Leslie Pack Kaelbling, Michael L.. (1996)(Correct)(367 citations)
to be accessible to researchers familiar with machine learning. Both the historical basis of the field and
attracted rapidly increasing interest in the machine learning and artificial intelligence communities. Its
Practical issues in temporal difference learning. Machine Learning, 8, 257-277. Tesauro, G. 1994) www.cs.cmu.edu/~reinf/www/../papers/survey.ps.gz
Irrelevant Features and the Subset Selection Problem - John, Kohavi, Pfleger (1994)(Correct)(270 citations)
in 1994, William W. Cohen &Haym Hirsh, eds.Machine Learning: Proceedings of the Eleventh International
and show that the definitions used in the machine learning literature do not adequately partition the
1990. Boolean feature discovery in empirical learning. Machine Learning 5:71-99. Quinlan, J. R. 1986. www.stanford.edu/~kpfleger/copy/publications/relevance4.ps.gz
Mixtures of Probabilistic Principal Component Analysers - Tipping, al. (1998)(Correct)(142 citations)
IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (3)281-293. Bregler, C. and S.
IEEE Transactions on Pattern Analysis and Machine Intelligence 16, 550-554. Japkowicz, N.C.
Nonlinear image interpolation using manifold learning. In G. Tesauro, D. S. Touretzky, and T. K. Leen neural-server.aston.ac.uk/Papers/postscript/NCRG_97_003.ps.Z
A System for Induction of Oblique Decision Trees - Murthy, Kasif, Salzberg (1994)(Correct)(120 citations)
challenge and opportunity for automated machine learning techniques. The advent of major scientific
one of the central techniques of experimental machine learning. Many variants of decision tree (DT)
Sigma Press, England. Nilsson, N. 1990)Learning Machines. Morgan Kaufmann, San Mateo, CA. Odewahn, www.cs.jhu.edu/~murthy/jair94.ps.Z
Toward Optimal Feature Selection - Koller, Sahami (1996)(Correct)(111 citations)
the issue of feature subset selection in machine learning. As defined by (John, Kohavi, Pfleger
not significantly correlated with the topic machine-learning. Therefore, if we were to run our algorithm robotics.stanford.edu/people/daphne/papers/ml96.ps