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ICASSP
2011
IEEE
12 years 10 months ago
Improving kernel-energy trade-offs for machine learning in implantable and wearable biomedical applications
Emerging biomedical sensors and stimulators offer unprecedented modalities for delivering therapy and acquiring physiological signals (e.g., deep brain stimulators). Exploiting th...
Kyong-Ho Lee, Sun-Yuan Kung, Naveen Verma
FLAIRS
2001
13 years 7 months ago
Improvement of Nearest-Neighbor Classifiers via Support Vector Machines
Theoretically well-founded, Support Vector Machines (SVM)are well-knownto be suited for efficiently solving classification problems. Althoughimprovedgeneralization is the maingoal...
Marc Sebban, Richard Nock
CVPR
2008
IEEE
14 years 8 months ago
Classification using intersection kernel support vector machines is efficient
Straightforward classification using kernelized SVMs requires evaluating the kernel for a test vector and each of the support vectors. For a class of kernels we show that one can ...
Subhransu Maji, Alexander C. Berg, Jitendra Malik
SETN
2010
Springer
14 years 1 months ago
A Feasibility Study on Low Level Techniques for Improving Parsing Accuracy for Spanish Using Maltparser
In the last years dependency parsing has been accomplished by machine learning–based systems showing great accuracy but usually under 90% for Labelled Attachment Score (LAS). Mal...
Miguel Ballesteros, Jesús Herrera, Virginia...
KDD
2004
ACM
179views Data Mining» more  KDD 2004»
14 years 6 months ago
1-dimensional splines as building blocks for improving accuracy of risk outcomes models
Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maxi...
David S. Vogel, Morgan C. Wang