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AAAI
2010
15 years 1 months ago
G-Optimal Design with Laplacian Regularization
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
ICCV
2007
IEEE
16 years 1 months ago
Locally Smooth Metric Learning with Application to Image Retrieval
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Dit-Yan Yeung, Hong Chang
ICML
2009
IEEE
16 years 15 days ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...
SIAMMAX
2010
105views more  SIAMMAX 2010»
14 years 6 months ago
Construction of Covariance Matrices with a Specified Discrepancy Function Minimizer, with Application to Factor Analysis
The main goal of this paper is to develop a numerical procedure for construction of covariance matrices such that for a given covariance structural model and a discrepancy function...
So Yeon Chun, A. Shapiro
ICML
2009
IEEE
16 years 15 days ago
Regularization and feature selection in least-squares temporal difference learning
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
J. Zico Kolter, Andrew Y. Ng