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PAKDD
2005
ACM
168views Data Mining» more  PAKDD 2005»
15 years 10 months ago
Adaptive Nonlinear Auto-Associative Modeling Through Manifold Learning
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
Junping Zhang, Stan Z. Li
IJCNN
2000
IEEE
15 years 9 months ago
Metrics that Learn Relevance
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...
Samuel Kaski, Janne Sinkkonen
ICPR
2010
IEEE
15 years 8 months ago
Learning a Joint Manifold Representation from Multiple Data Sets
—The problem we address in the paper is how to learn a joint representation from data lying on multiple manifolds. We are given multiple data sets and there is an underlying comm...
Marwan Torki, Ahmed Elgammal, Chan-Su Lee
134
Voted
ECAI
2008
Springer
15 years 6 months ago
Exploiting locality of interactions using a policy-gradient approach in multiagent learning
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...
Francisco S. Melo
105
Voted
ICALT
2005
IEEE
15 years 10 months ago
Goal Oriented Personalisation with SCORM
This paper presents an innovative approach to personalize on-line content to the needs of individual learners. We use a regular educational environment, the BlackboardTM Learning ...
Guillermo Power, Hugh C. Davis, Alexandra I. Crist...