Maximum likelihood competitive learning

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Maximum likelihood competitive learning

Source

Advances in neural information processing systems 2 book contents

Pages: 574 - 582

Year of Publication: 1990

ISBN:1-55860-100-7

Author

Steven J. Nowlan

Publisher

Morgan Kaufmann Publishers Inc. San Francisco, CA, USA

Bibliometrics

Downloads (6 Weeks): n/a, Downloads (12 Months): n/a, Citation Count: 16

Additional Information:

cited by index terms collaborative colleagues

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CITED BY 16

	John B. Hampshire, II , Alex Waibel, The Meta-Pi Network: Building Distributed Knowledge Representations for Robust Multisource Pattern Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.14 n.7, p.751-769, July 1992
	Volker Tresp , Jürgen Hollatz , Subutai Ahmad, Representing Probabilistic Rules with Networks of GaussianBasis Functions, Machine Learning, v.27 n.2, p.173-200, May 1997
	Janne Sinkkonen , Samuel Kaski, Clustering based on conditional distributions in an auxiliary space, Neural Computation, v.14 n.1, p.217-239, January 2002
	Robert A. Jacobs , Michael I. Jordan , Steven J. Nowlan , Geoffrey E. Hinton, Adaptive mixtures of local experts, Neural Computation, v.3 n.1, p.79-87, Spring 1991
	Rajesh P. N. Rao , Olac Fuentes, Hierarchical Learning of Navigational Behaviors in anAutonomous Robot using a Predictive Sparse DistributedMemory, Machine Learning, v.31 n.1-3, p.87-113, April/May/June 1998
	Laurenz Wiskott , Terrence Sejnowski, Constrained optimization for neural map formation: a unifying framework for weight growth and normalization, Neural Computation, v.10 n.3, p.671-716, April 1998
	Sam Roweis , Zoubin Ghahramani, A unifying review of linear Gaussian models, Neural Computation, v.11 n.2, p.305-345, Feb. 15, 1999
	Suzanna Becker, Implicit learning in 3D object recognition: the importance of temporal context, Neural Computation, v.11 n.2, p.347-374, Feb. 15, 1999
	Akio Utsugi, Hyperparameter selection for self-organizing maps, Neural Computation, v.9 n.3, p.623-635, April 1, 1997
	Randall C. O'reilly, Generalization in Interactive Networks: The Benefits of Inhibitory Competition and Hebbian Learning, Neural Computation, v.13 n.6, p.1199-1241, June 2001
	Marc M. Van Hulle, Kernel-based equiprobabilistic topographic map formation, Neural Computation, v.10 n.7, p.1847-1871, Oct. 1998
	Rajesh P. N. Rao , Olac Fuentes, Hierarchical Learning of Navigational Behaviors in anAutonomous Robot using a Predictive Sparse Distributed Memory, Autonomous Robots, v.5 n.3-4, p.297-316, July-August 1998
	Mutaz M. Jafar , Ali Zilouchian, Prediction of Critical Desalination Parameters Using Radial Basis Functions Networks, Journal of Intelligent and Robotic Systems, v.34 n.2, p.219-230, June 2002
	Vassilios Petridis , Athanasios Kehagias, A recurrent network implementation of time series classification, Neural Computation, v.8 n.2, p.357-372, February 15, 1996
	Dimitry Gorinevsky , Thomas H. Connolly, Comparison of some neural network and scattered data approximations: The inverse manipulator kinematics example, Neural Computation, v.6 n.3, p.521-542, May 1994
	Jörg Lücke , Maneesh Sahani, Maximal Causes for Non-linear Component Extraction, The Journal of Machine Learning Research, 9, p.1227-1267, 6/1/2008