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» A Model Selection Approach for Local Learning
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NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 8 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
PLDI
2011
ACM
12 years 11 months ago
Isolating and understanding concurrency errors using reconstructed execution fragments
In this paper we propose Recon, a new general approach to concurrency debugging. Recon goes beyond just detecting bugs, it also presents to the programmer short fragments of buggy...
Brandon Lucia, Benjamin P. Wood, Luis Ceze
CVPR
2012
IEEE
11 years 11 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
TIP
2010
255views more  TIP 2010»
13 years 3 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
GLOBECOM
2008
IEEE
14 years 3 months ago
Optimal Location Updates in Mobile Ad Hoc Networks: A Separable Cost Case
Abstract—We consider the location service in a mobile adhoc network (MANET), where each node needs to maintain its location information in the network by (i) frequently updating ...
Zhenzhen Ye, Alhussein A. Abouzeid