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AI
2002
Springer
15 years 7 months ago
Learning cost-sensitive active classifiers
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
Russell Greiner, Adam J. Grove, Dan Roth
TIP
2010
155views more  TIP 2010»
15 years 6 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
BMVC
2010
15 years 2 months ago
Saliency Segmentation based on Learning and Graph Cut Refinement
Saliency detection is a well researched problem in computer vision. In previous work, most of the effort is spent on manually devising a saliency measure. Instead we propose a sim...
Paria Mehrani, Olga Veksler
SIAMJO
2010
127views more  SIAMJO 2010»
15 years 2 months ago
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye
EUROGP
2007
Springer
116views Optimization» more  EUROGP 2007»
16 years 1 months ago
Genetic Programming with Fitness Based on Model Checking
Abstract. Model checking is a way of analysing programs and programlike structures to decide whether they satisfy a list of temporal logic statements describing desired behaviour. ...
Colin G. Johnson