Learning random log-depth decision trees under uniform distribution

SIAM Journal on Computing

Volumn 34, Issue 5, 2005, Pages 1107-1128

  Jackson, Jeffrey C ^a   Servedio, Rocco A ^b  

^a DUQUESNE UNIVERSITY   (United States)

^b Department of Earth and Environmental Sciences   (United States)

Author keywords

Computational learning theory; Decision trees; PAC learning

Indexed keywords

COMPUTATIONAL LEARNING THEORY; DECISION TREES; PAC LEARNING; POLYNOMIAL FRACTIONS;

BOOLEAN FUNCTIONS; LEARNING SYSTEMS; MATHEMATICAL MODELS; POLYNOMIALS; RANDOM PROCESSES; TREES (MATHEMATICS);

DECISION THEORY;

EID: 27144557996     PISSN: 00975397     EISSN: None     Source Type: Journal    
DOI: 10.1137/S0097539704444555     Document Type: Article

References (10)

1. A. BLUM, Rank-r decision trees are a subclass of r-decision lists, Inform. Process. Lett., 42 (1992), pp. 83-185.
2. A. BLUM, M. FURST, M. KEARNS, AND R. LIPTON, Cryptographic primitives based on hard learning problems, in Advances in Cryptology - CRYPTO'93, Lecture Notes in Comput. Sci. 773, Springer, Berlin, 1994, pp. 278-291.
3. A. BLUM, M. FURST, J. JACKSON, M. KEARNS, Y. MANSOUR, AND S. RUDICH, Weakly learning DNF and characterizing statistical query learning using Fourier analysis, in Proceedings of the 26th Annual ACM Symposium on Theory of Computing, ACM, New York, 1994, pp. 253-262.
4. L. BREIMAN, J. FRIEDMAN, R. OLSHEN, AND C. STONE, Classification of Regression Trees, Wadsworth, Belmont, CA, 1984.
5. N. BSHOUTY, Exact learning boolean functions via the monotone theory, Inform. and Comput., 123 (1995), pp. 146-153.
6. A. EHRENFEUCHT AND D. HAUSSLER, Learning decision trees from random examples, Inform. and Comput., 82 (1989), pp. 231-246.
7. T. HANCOCK, Learning kμ decision trees on the uniform distribution, in Proceedings of the 6th Annual ACM Conference on Computational Learning Theory, ACM, New York, 1993, pp. 352-360.
8. J. JACKSON AND R. SERVEDIO, Learning random log-depth decision trees under the uniform distribution, in Proceedings of the 16th Annual Conference on Computational Learning Theory, Lecture Notes in Comput. Sci. 2777, Springer, Berlin, 2003, pp. 610-624.
9. E. KUSHILEVITZ AND Y. MANSOUR, Learning decision trees using the Fourier spectrum, SIAM J. Comput., 22 (1993), pp. 1331-1348.
10. J. QUINLAN, C4.5: Programs for Machine Learning, Morgan-Kaufmann, San Mateo, CA, 1993.