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» On Kernel Methods for Relational Learning
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ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 2 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
AAAI
2010
15 years 4 months ago
Relative Entropy Policy Search
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature conv...
Jan Peters, Katharina Mülling, Yasemin Altun
125
Voted
ICPR
2006
IEEE
16 years 4 months ago
A maximum margin discriminative learning algorithm for temporal signals
We propose a new maximum margin discriminative learning algorithm here for classification of temporal signals. It is superior to conventional HMM in the sense that it does not nee...
Wenjie Xu, Jiankang Wu, Zhiyong Huang
105
Voted
TSP
2008
89views more  TSP 2008»
15 years 3 months ago
The Kernel Least-Mean-Square Algorithm
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
Weifeng Liu, Puskal P. Pokharel, Jose C. Principe
ICML
2003
IEEE
16 years 4 months ago
The Cross Entropy Method for Fast Policy Search
We present a learning framework for Markovian decision processes that is based on optimization in the policy space. Instead of using relatively slow gradient-based optimization al...
Shie Mannor, Reuven Y. Rubinstein, Yohai Gat