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Common terms and phrasesADABOOST Advances in Neural analysis applied approach approximation assume average Bayesian belief propagation bound classifier components Computer Computer Vision constraints convergence corresponding covariance datasets defined denote density dimensionality distance distribution dynamics eigenvalues eigenvectors embedding entropy error estimate evaluated experiments feature Figure Gaussian given graph Hidden Markov Model IEEE Information Processing Systems input Isomap iteration kernel labels learning algorithms linear logistic regression Machine Learning manifold margin Markov Markov network matrix method metric minimize mixture mixture model Neural Information Processing neural networks neuron node noise nonlinear object observed obtained optimal output parameters patches patterns perceptron performance pixels points posterior prediction probabilistic probability problem proposed random regression representation sample segmentation selection semi-supervised semi-supervised learning sequence signal solution space spectral clustering spike statistical structure subset support vector support vector machines synaptic Theorem training set update variables variance weight References from web pagesAdvances in Neural Information Processing Systems 17 - The MIT Press Advances in Neural Information Processing Systems 17 papers:nips-2005 [Léon Bottou] Publications MPIK Tuebingen Publications Neural Information Processing Group, TU-Berlin Publications NEC -- Machine Learning Department -- Publications Recent Publications of Michael C. Mozer Peter Bartlett | EECS at UC Berkeley Publication List Bibliographic information
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