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NIPS
1998
13 years 11 months ago
Robot Docking Using Mixtures of Gaussians
This paper applies the Mixture of Gaussians probabilistic model, combined with Expectation Maximization optimization to the task of summarizing three dimensional range data for a ...
Matthew M. Williamson, Roderick Murray-Smith, Volk...
NIPS
1998
13 years 11 months ago
Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
Tony Jebara, Alex Pentland
NIPS
1998
13 years 11 months ago
Inference in Multilayer Networks via Large Deviation Bounds
We study probabilistic inference in large, layered Bayesian networks represented as directed acyclic graphs. We show that the intractability of exact inference in such networks do...
Michael J. Kearns, Lawrence K. Saul
NIPS
1998
13 years 11 months ago
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This paper proposes an algorithm for training SVMs: Sequential Mi...
John C. Platt
NIPS
1998
13 years 11 months ago
Global Optimisation of Neural Network Models via Sequential Sampling
We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
João F. G. de Freitas, Mahesan Niranjan, Ar...