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» On learning algorithm selection for classification
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ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 12 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
BMVC
2010
15 years 4 months ago
Joint Modeling of Algorithm Behavior and Image Quality for Algorithm Performance Prediction
In this paper, we propose a framework for predicting the performance of a vision algorithm given the input image or video so as to maximize the algorithm's ability to provide...
Apurva Gala, Shishir Shah
ECCV
2010
Springer
15 years 10 months ago
Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification
Abstract. Much recent research in human activity recognition has focused on the problem of recognizing simple repetitive (walking, running, waving) and punctual actions (sitting up...
PRL
2008
152views more  PRL 2008»
15 years 6 months ago
WND-CHARM: Multi-purpose image classification using compound image transforms
We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classificati...
Nikita Orlov, Lior Shamir, Tomasz J. Macura, Josia...
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
16 years 7 months ago
Effective label acquisition for collective classification
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Mustafa Bilgic, Lise Getoor