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ICCV
2009
IEEE
15 years 3 months ago
Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds
We present a manifold learning approach to dimensionality reduction that explicitly models the manifold as a mapping from low to high dimensional space. The manifold is represen...
Samuel Gerber, Tolga Tasdizen, Ross Whitaker
ATAL
2005
Springer
14 years 4 months ago
Rapid on-line temporal sequence prediction by an adaptive agent
Robust sequence prediction is an essential component of an intelligent agent acting in a dynamic world. We consider the case of near-future event prediction by an online learning ...
Steven Jensen, Daniel Boley, Maria L. Gini, Paul R...
IMC
2004
ACM
14 years 4 months ago
An analysis of live streaming workloads on the internet
In this paper, we study the live streaming workload from a large content delivery network. Our data, collected over a 3 month period, contains over 70 million requests for 5,000 d...
Kunwadee Sripanidkulchai, Bruce M. Maggs, Hui Zhan...
ICCV
2007
IEEE
15 years 22 days ago
The Joint Manifold Model for Semi-supervised Multi-valued Regression
Many computer vision tasks may be expressed as the problem of learning a mapping between image space and a parameter space. For example, in human body pose estimation, recent rese...
Ramanan Navaratnam, Andrew W. Fitzgibbon, Roberto ...
AAAI
2011
12 years 10 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi