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» Sampling Techniques for Kernel Methods
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VLDB
2000
ACM
120views Database» more  VLDB 2000»
15 years 1 months ago
Integrating the UB-Tree into a Database System Kernel
Multidimensional access methods have shown high potential for significant performance improvements in various application domains. However, only few approaches have made their way...
Frank Ramsak, Volker Markl, Robert Fenk, Martin Zi...
AAAI
2008
15 years 6 days ago
Sketch Recognition Based on Manifold Learning
Current feature-based methods for sketch recognition systems rely on human-selected features. Certain machine learning techniques have been found to be good nonlinear features ext...
Heeyoul Choi, Tracy Hammond
JMLR
2010
147views more  JMLR 2010»
14 years 4 months ago
Image Denoising with Kernels Based on Natural Image Relations
A successful class of image denoising methods is based on Bayesian approaches working in wavelet representations. The performance of these methods improves when relations among th...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...
TKDE
2012
270views Formal Methods» more  TKDE 2012»
13 years 8 days ago
Low-Rank Kernel Matrix Factorization for Large-Scale Evolutionary Clustering
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...
ECML
2007
Springer
15 years 4 months ago
Roulette Sampling for Cost-Sensitive Learning
In this paper, we propose a new and general preprocessor algorithm, called CSRoulette, which converts any cost-insensitive classification algorithms into cost-sensitive ones. CSRou...
Victor S. Sheng, Charles X. Ling