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» A Training Method with Small Computation for Classification
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KDD
2010
ACM
222views Data Mining» more  KDD 2010»
13 years 9 months ago
Large linear classification when data cannot fit in memory
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-J...
JUCS
2008
130views more  JUCS 2008»
13 years 7 months ago
Feature Selection for the Classification of Large Document Collections
: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of...
Janez Brank, Dunja Mladenic, Marko Grobelnik, Nata...
CVPR
2010
IEEE
14 years 7 days ago
Taxonomic Classification for Web-based Videos
Categorizing web-based videos is an important yet challenging task. The difficulties arise from large data diversity within a category, lack of labeled data, and degradation of vi...
Yang Song, Ming Zhao, Jay Yagnik, Xiaoyun Wu
IEEEMM
2007
146views more  IEEEMM 2007»
13 years 7 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
ICPR
2004
IEEE
14 years 9 months ago
A Pattern Synthesis Technique with an Efficient Nearest Neighbor Classifier for Binary Pattern Recognition
Important factors affecting the efficiency and performance of the nearest neighbor classifier (NNC) are space, classification time requirements and for high dimensional data, due ...
M. Narasimha Murty, P. Viswanath, Shalabh Bhatnaga...