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» Predicting relative performance of classifiers from samples
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HVEI
2010
13 years 7 months ago
Quantifying the relationship between visual salience and visual importance
This paper presents the results of two psychophysical experiments and an associated computational analysis designed to quantify the relationship between visual salience and visual...
Junle Wang, Damon M. Chandler, Patrick Le Callet
CVPR
2007
IEEE
14 years 11 months ago
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists...
Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau,...
ICDE
2008
IEEE
165views Database» more  ICDE 2008»
14 years 10 months ago
Online Failure Forecast for Fault-Tolerant Data Stream Processing
In this paper, we present a new online failure forecast system to achieve predictive failure management for fault-tolerant data stream processing. Different from previous reactive ...
Xiaohui Gu, Spiros Papadimitriou, Philip S. Yu, Sh...
CSL
2007
Springer
13 years 9 months ago
Modeling durations of syllables using neural networks
In this paper, we propose a neural network model for predicting the durations of syllables. A four layer feedforward neural network trained with backpropagation algorithm is used ...
K. Sreenivasa Rao, B. Yegnanarayana
LREC
2008
78views Education» more  LREC 2008»
13 years 10 months ago
Approximating Learning Curves for Active-Learning-Driven Annotation
Active learning (AL) is getting more and more popular as a methodology to considerably reduce the annotation effort when building training material for statistical learning method...
Katrin Tomanek, Udo Hahn