78 search results - page 8 / 16 » Smooth Bayesian Kernel Machines |
117
Voted
ECML
2006
Springer
15 years 6 months ago
2006
Springer
Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
124
Voted
PAA
2010
15 years 29 days ago
2010
By applying recent results in optimization theory variously known as optimization transfer or majorize/minimize algorithms, an algorithm for binary, kernel, Fisher discriminant ana...
146
Voted
ML
2002
ACM
15 years 2 months ago
2002
ACM
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...
145
Voted
ICML
2010
IEEE
15 years 3 months ago
2010
IEEE
Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumpti...
130
Voted
ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
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 ...