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ICML
2004
IEEE
15 years 3 months ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
NIPS
2008
14 years 11 months ago
2008
We study the convergence and the rate of convergence of a local manifold learning algorithm: LTSA [13]. The main technical tool is the perturbation analysis on the linear invarian...
ICPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Complex simulations can generate very large amounts of data stored disjointly across many local disks. Learning from this data can be problematic due to the difficulty of obtainin...
IJCNN
2006
IEEE
15 years 4 months ago
2006
IEEE
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
MLCW
2005
Springer
15 years 3 months ago
2005
Springer
In this paper we present lessons learned in the Evaluating Predictive Uncertainty Challenge. We describe the methods we used in regression challenges, including our winning method ...