Four Types of Learning Curves
暂无分享,去创建一个
[1] A. A. Mullin,et al. Principles of neurodynamics , 1962 .
[2] Shun-ichi Amari,et al. A Theory of Adaptive Pattern Classifiers , 1967, IEEE Trans. Electron. Comput..
[3] K. Abromeit. Music Received , 2023, Notes.
[4] Leslie G. Valiant,et al. A theory of the learnable , 1984, STOC '84.
[5] Shun-ichi Amari,et al. Differential-geometrical methods in statistics , 1985 .
[6] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[7] J. Rissanen. Stochastic Complexity and Modeling , 1986 .
[8] David Haussler,et al. Predicting {0,1}-functions on randomly drawn points , 1988, COLT '88.
[9] Esther Levin,et al. A statistical approach to learning and generalization in layered neural networks , 1989, Proc. IEEE.
[10] David Haussler,et al. What Size Net Gives Valid Generalization? , 1989, Neural Computation.
[11] Halbert White,et al. Learning in Artificial Neural Networks: A Statistical Perspective , 1989, Neural Computation.
[12] Eric B. Baum,et al. The Perceptron Algorithm is Fast for Nonmalicious Distributions , 1990, Neural Computation.
[13] Shun-ichi Amari,et al. Mathematical foundations of neurocomputing , 1990, Proc. IEEE.
[14] Sompolinsky,et al. Learning from examples in large neural networks. , 1990, Physical review letters.
[15] Haim Sompolinsky,et al. Learning from Examples in a Single-Layer Neural Network , 1990 .
[16] Vijay K. Samalam,et al. Exhaustive Learning , 1990, Neural Computation.
[17] Shun-ichi Amari,et al. Dualistic geometry of the manifold of higher-order neurons , 1991, Neural Networks.
[18] Sompolinsky,et al. Statistical mechanics of learning from examples. , 1992, Physical review. A, Atomic, molecular, and optical physics.
[19] Shun-ichi Amari,et al. Information geometry of Boltzmann machines , 1992, IEEE Trans. Neural Networks.
[20] Yoshiyuki Kabashima,et al. Learning Curves for Error Minimum and Maximum Likelihood Algorithms , 1992, Neural Computation.
[21] Shun-ichi Amari,et al. Statistical Theory of Learning Curves under Entropic Loss Criterion , 1993, Neural Computation.
[22] H. Sebastian Seung,et al. Learning from a Population of Hypotheses , 1993, COLT '93.
[23] Oh,et al. Generalization in a two-layer neural network. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[24] Shun-ichi Amari,et al. A universal theorem on learning curves , 1993, Neural Networks.