AAAI
2012
11 years 7 months ago
2012
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
SDM
2012
SIAM
11 years 7 months ago
2012
SIAM
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
CVPR
2012
IEEE
11 years 7 months ago
2012
IEEE
In this article, we focus on the problem of large-scale instance-level image retrieval. For efficiency reasons, it is common to represent an image by a fixed-length descriptor w...
PAMI
2012
11 years 7 months ago
2012
— This paper addresses the problem of large-scale image search. Three constraints have to be taken into account: search accuracy, efficiency, and memory usage. We first present...
ICDE
2012
IEEE
11 years 7 months ago
2012
IEEE
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...
ICDE
2012
IEEE
11 years 7 months ago
2012
IEEE
—Dimensionality reduction is essential in text mining since the dimensionality of text documents could easily reach several tens of thousands. Most recent efforts on dimensionali...
JMLR
2012
11 years 7 months ago
2012
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
WACV
2012
IEEE
12 years 1 months ago
2012
IEEE
We present a novel algorithm, Compact Kd-Trees (CompactKdt), that achieves state-of-the-art performance in searching large scale object image collections. The algorithm uses an or...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the p-norm of the parameters. We discuss several implications ...
ICCV
2011
IEEE
12 years 5 months ago
2011
IEEE
Non-rigid structure from motion (NRSFM) is a difficult, underconstrained problem in computer vision. The standard approach in NRSFM constrains 3D shape deformation using a linear...