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TIP
2008
213views more  TIP 2008»
13 years 5 months ago
Deblurring Using Regularized Locally Adaptive Kernel Regression
Kernel regression is an effective tool for a variety of image processing tasks such as denoising and interpolation [1]. In this paper, we extend the use of kernel regression for de...
Hiroyuki Takeda, Sina Farsiu, Peyman Milanfar
CLUSTER
2002
IEEE
14 years 11 days ago
Kernel-Level Caching for Optimizing I/O by Exploiting Inter-Application Data Sharing
With applications becoming larger and the increasing load on high performance systems, it is important to tackle the I/O bottleneck problem from several angles. It is not only ess...
Murali Vilayannur, Mahmut T. Kandemir, Anand Sivas...
ICASSP
2011
IEEE
12 years 11 months ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
CORR
2010
Springer
107views Education» more  CORR 2010»
13 years 7 months ago
Fast GPGPU Data Rearrangement Kernels using CUDA
: Many high performance computing algorithms are bandwidth limited, hence the need for optimal data rearrangement kernels as well as their easy integration into the rest of the app...
Michael Bader, Hans-Joachim Bungartz, Dheevatsa Mu...
IJCNN
2007
IEEE
14 years 1 months ago
Symmetric Kernel Detector for Multiple-Antenna Aided Beamforming Systems
— We propose a powerful symmetric kernel classifier for nonlinear detection in challenging rank-deficient multipleantenna aided communication systems. By exploiting the inheren...
Sheng Chen, Andreas Wolfgang, Chris J. Harris, Laj...