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» A Practical Method for the Sparse Resultant
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JMLR
2011
192views more  JMLR 2011»
14 years 4 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
IWSOC
2005
IEEE
112views Hardware» more  IWSOC 2005»
15 years 3 months ago
Practical Techniques for Performance Estimation of Processors
Performance estimation of processor is important to select the right processor for an application. Poorly chosen processors can either under perform very badly or over perform but...
Abhijit Ray, Thambipillai Srikanthan, Wu Jigang
ECCV
2010
Springer
15 years 2 months ago
Practical Autocalibration
As it has been noted several times in literature, the difficult part of autocalibration efforts resides in the structural non-linearity of the search for the plane at infinity. I...
CVPR
2008
IEEE
15 years 12 months ago
Transfer learning for image classification with sparse prototype representations
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...
Ariadna Quattoni, Michael Collins, Trevor Darrell
ECCV
2008
Springer
15 years 12 months ago
Sparse Long-Range Random Field and Its Application to Image Denoising
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Yunpeng Li, Daniel P. Huttenlocher