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ICML
2006
IEEE
16 years 4 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
AAAI
2008
15 years 6 months ago
Dimension Amnesic Pyramid Match Kernel
With the success of local features in object recognition, feature-set representations are widely used in computer vision and related domains. Pyramid match kernel (PMK) is an effi...
Yi Liu, Xulei Wang, Hongbin Zha
ICIP
2006
IEEE
16 years 5 months ago
Using Non-Parametric Kernel to Segment and Smooth Images Simultaneously
Piecewise constant and piecewise smooth Mumford-Shah (MS) models have been widely studied and used for image segmentation. More complicated than piecewise constant MS, global Gaus...
Weihong Guo, Yunmei Chen
COLT
2003
Springer
15 years 9 months ago
Maximum Margin Algorithms with Boolean Kernels
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
Roni Khardon, Rocco A. Servedio
ILP
2003
Springer
15 years 9 months ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon