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141
Voted
CVPR
2010
IEEE
15 years 4 months ago
Learning kernels for variants of normalized cuts: Convex relaxations and applications
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Chr...
TCBB
2008
120views more  TCBB 2008»
15 years 4 months ago
Learning Scoring Schemes for Sequence Alignment from Partial Examples
When aligning biological sequences, the choice of scoring scheme is critical. Even small changes in gap penalties, for example, can yield radically different alignments. A rigorous...
Eagu Kim, John D. Kececioglu
140
Voted
AI
2002
Springer
15 years 4 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
174
Voted
TIP
2010
155views more  TIP 2010»
15 years 3 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
14 years 11 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