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» Latent Process Model for Manifold Learning
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ICML
2007
IEEE
16 years 15 days ago
Learning state-action basis functions for hierarchical MDPs
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...
Sarah Osentoski, Sridhar Mahadevan
KDD
2012
ACM
254views Data Mining» more  KDD 2012»
13 years 2 months ago
Playlist prediction via metric embedding
Digital storage of personal music collections and cloud-based music services (e.g. Pandora, Spotify) have fundamentally changed how music is consumed. In particular, automatically...
Shuo Chen, Josh L. Moore, Douglas Turnbull, Thorst...
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
16 years 3 days ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
ICASSP
2011
IEEE
14 years 3 months ago
A hierarchical generative model for Generic Audio Document Categorization
In this paper, we call the pattern classification problem that consists in assigning a category label to a long audio signal based on its semantic content as Generic Audio Documen...
Zhi Zeng, Shuwu Zhang
CVPR
2007
IEEE
16 years 1 months ago
Unsupervised Activity Perception by Hierarchical Bayesian Models
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Xiaogang Wang, Xiaoxu Ma, Eric Grimson