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» Kernels for Generalized Multiple-Instance Learning
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ILP
2003
Springer
14 years 1 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
ICDM
2003
IEEE
153views Data Mining» more  ICDM 2003»
14 years 1 months ago
Dimensionality Reduction Using Kernel Pooled Local Discriminant Information
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
Peng Zhang, Jing Peng, Carlotta Domeniconi
ICPR
2006
IEEE
14 years 9 months ago
Weakly Supervised Learning on Pre-image Problem in Kernel Methods
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
Weishi Zheng, Jian-Huang Lai, Pong Chi Yuen
ICASSP
2009
IEEE
14 years 3 months ago
Space Kernel Analysis
In this paper, we propose a novel nonparametric modeling technique, namely Space Kernel Analysis (SKA), as a result of the definition of the space kernel. We analyze the uncertai...
Liuling Gong, Dan Schonfeld
ICML
2007
IEEE
14 years 9 months ago
More efficiency in multiple kernel learning
An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes ...
Alain Rakotomamonjy, Francis Bach, Stéphane...