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KDD
2012
ACM
207views Data Mining» more  KDD 2012»
13 years 10 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
CIKM
2010
Springer
15 years 6 months ago
Novel local features with hybrid sampling technique for image retrieval
In image retrieval, most existing approaches that incorporate local features produce high dimensional vectors, which lead to a high computational and data storage cost. Moreover, ...
Leszek Kaliciak, Dawei Song, Nirmalie Wiratunga, J...
ICCV
2011
IEEE
14 years 7 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
TKDE
2012
192views Formal Methods» more  TKDE 2012»
13 years 9 months ago
Discriminative Feature Selection by Nonparametric Bayes Error Minimization
Feature selection is fundamental to knowledge discovery from massive amount of high-dimensional data. In an effort to establish theoretical justification for feature selection al...
Shuang-Hong Yang, Bao-Gang Hu
ICCV
2001
IEEE
16 years 9 months ago
Learning the Semantics of Words and Pictures
We present a statistical model for organizing image collections which integrates semantic information provided by associated text and visual information provided by image features...
Kobus Barnard, David A. Forsyth