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» Smooth Bayesian Kernel Machines
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ECML
2006
Springer
14 years 3 days ago
Fisher Kernels for Relational Data
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Uwe Dick, Kristian Kersting
PAA
2010
13 years 6 months ago
A simple iterative algorithm for parsimonious binary kernel Fisher discrimination
By applying recent results in optimization theory variously known as optimization transfer or majorize/minimize algorithms, an algorithm for binary, kernel, Fisher discriminant ana...
Robert F. Harrison, Kitsuchart Pasupa
ML
2002
ACM
163views Machine Learning» more  ML 2002»
13 years 8 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
ICML
2010
IEEE
13 years 9 months ago
An Analysis of the Convergence of Graph Laplacians
Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumpti...
Daniel Ting, Ling Huang, Michael I. Jordan
ICML
2007
IEEE
14 years 9 months ago
Bayesian actor-critic algorithms
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
Mohammad Ghavamzadeh, Yaakov Engel