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» Supervised feature selection via dependence estimation
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SIGMOD
1999
ACM
110views Database» more  SIGMOD 1999»
13 years 11 months ago
Multi-dimensional Selectivity Estimation Using Compressed Histogram Information
The database query optimizer requires the estimation of the query selectivity to find the most efficient access plan. For queries referencing multiple attributes from the same rel...
Ju-Hong Lee, Deok-Hwan Kim, Chin-Wan Chung
NIPS
2007
13 years 8 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
ICCV
2007
IEEE
14 years 9 months ago
3D generic object categorization, localization and pose estimation
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...
Silvio Savarese, Fei-Fei Li 0002
COLING
2010
13 years 2 months ago
Boosting Relation Extraction with Limited Closed-World Knowledge
This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation...
Feiyu Xu, Hans Uszkoreit, Sebastian Krause, Hong L...
ICCV
2005
IEEE
14 years 1 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla