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» Local Minimax Learning of Approximately Polynomial Functions
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IJCNN
2000
IEEE
13 years 12 months ago
Piecewise Linear Homeomorphisms: The Scalar Case
The class of piecewise linear homeomorphisms (PLH) provides a convenient functional representation for many applications wherein an approximation to data is required that is inver...
Richard E. Groff, Daniel E. Koditschek, Pramod P. ...
FOCS
1989
IEEE
13 years 11 months ago
Constant Depth Circuits, Fourier Transform, and Learnability
In this paper, Boolean functions in ,4C0 are studied using harmonic analysis on the cube. The main result is that an ACO Boolean function has almost all of its “power spectrum”...
Nathan Linial, Yishay Mansour, Noam Nisan
COLT
2010
Springer
13 years 5 months ago
Toward Learning Gaussian Mixtures with Arbitrary Separation
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Mikhail Belkin, Kaushik Sinha
JMLR
2008
150views more  JMLR 2008»
13 years 7 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 1 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...