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AAAI
2012
7 years 2 months ago
Sparse Probabilistic Relational Projection
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
Wu-Jun Li, Dit-Yan Yeung
SDM
2012
SIAM
261views Data Mining» more  SDM 2012»
7 years 2 months ago
Combining Active Learning and Dynamic Dimensionality Reduction
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...
Mustafa Bilgic
CVPR
2012
IEEE
7 years 2 months ago
Leveraging category-level labels for instance-level image retrieval
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...
Albert Gordo, José A. Rodríguez-Serr...
PAMI
2012
7 years 2 months ago
Aggregating Local Image Descriptors into Compact Codes
— 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...
Hervé Jégou, Florent Perronnin, Matt...
ICDE
2012
IEEE
246views Database» more  ICDE 2012»
7 years 2 months ago
HiCS: High Contrast Subspaces for Density-Based Outlier Ranking
—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...
Fabian Keller, Emmanuel Müller, Klemens B&oum...
ICDE
2012
IEEE
227views Database» more  ICDE 2012»
7 years 2 months ago
Horizontal Reduction: Instance-Level Dimensionality Reduction for Similarity Search in Large Document Databases
—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...
Min-Soo Kim 0001, Kyu-Young Whang, Yang-Sae Moon
JMLR
2012
7 years 2 months ago
Metric and Kernel Learning Using a Linear Transformation
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...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
WACV
2012
IEEE
7 years 7 months ago
CompactKdt: Compact signatures for accurate large scale object recognition
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...
Mohamed Aly, Mario E. Munich, Pietro Perona
CORR
2012
Springer
198views Education» more  CORR 2012»
7 years 7 months ago
Lipschitz Parametrization of Probabilistic Graphical Models
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 ...
Jean Honorio
ICCV
2011
IEEE
8 years 5 days ago
Kernel Non-Rigid Structure from Motion
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...
Paulo F. U. Gotardo, Aleix M. Martinez
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