Toward efficient agnostic learning
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[1] W. Hoeffding. Probability Inequalities for sums of Bounded Random Variables , 1963 .
[2] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[3] R. Dudley. Central Limit Theorems for Empirical Measures , 1978 .
[4] David S. Johnson,et al. Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .
[5] M. Garey. Johnson: computers and intractability: a guide to the theory of np- completeness (freeman , 1979 .
[6] D. Pollard. Convergence of stochastic processes , 1984 .
[7] Leslie G. Valiant,et al. A theory of the learnable , 1984, STOC '84.
[8] Leslie G. Valiant,et al. Learning Disjunction of Conjunctions , 1985, IJCAI.
[9] Leslie G. Valiant,et al. On the learnability of Boolean formulae , 1987, STOC.
[10] Leslie G. Valiant,et al. Computational limitations on learning from examples , 1988, JACM.
[11] M. Kearns,et al. Crytographic limitations on learning Boolean formulae and finite automata , 1989, STOC '89.
[12] Halbert White,et al. Learning in Artificial Neural Networks: A Statistical Perspective , 1989, Neural Computation.
[13] David Haussler,et al. Learnability and the Vapnik-Chervonenkis dimension , 1989, JACM.
[14] A Markovian extension of Valiant's learning model , 1990, Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science.
[15] Kenji Yamanishi,et al. A learning criterion for stochastic rules , 1990, COLT '90.
[16] A. Izenman. Review Papers: Recent Developments in Nonparametric Density Estimation , 1991 .
[17] Philip M. Long,et al. Tracking drifting concepts using random examples , 1991, Annual Conference Computational Learning Theory.
[18] A. Izenman. Recent Developments in Nonparametric Density Estimation , 1991 .
[19] Jorma Rissanen,et al. Density estimation by stochastic complexity , 1992, IEEE Trans. Inf. Theory.
[20] Yoav Freund,et al. An improved boosting algorithm and its implications on learning complexity , 1992, COLT '92.
[21] Avrim Blum,et al. Learning switching concepts , 1992, COLT '92.
[22] David Haussler,et al. Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications , 1992, Inf. Comput..
[23] Ming Li,et al. Learning in the Presence of Malicious Errors , 1993, SIAM J. Comput..
[24] Noam Nisan,et al. Constant depth circuits, Fourier transform, and learnability , 1993, JACM.
[25] Leslie G. Valiant,et al. Cryptographic limitations on learning Boolean formulae and finite automata , 1994, JACM.
[26] Robert E. Schapire,et al. Efficient distribution-free learning of probabilistic concepts , 1990, Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science.