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» Estimating Predictive Variances with Kernel Ridge Regression
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NIPS
2003
14 years 10 months ago
Kernel Dimensionality Reduction for Supervised Learning
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
NIPS
2004
14 years 10 months ago
A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities
We devise and experiment with a dynamical kernel-based system for tracking hand movements from neural activity. The state of the system corresponds to the hand location, velocity,...
Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaa...
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
15 years 1 months ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...
ICPR
2008
IEEE
15 years 3 months ago
A 2D model for face superresolution
Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
B. G. Vijay Kumar, Rangarajan Aravind
PROMISE
2010
14 years 4 months ago
Modeling the relationship between software effort and size using deming regression
Background: The relation between software effort and size has been modeled in literature as exponential, in the sense that the natural logarithm of effort is expressed as a linear...
Nikolaos Mittas, Makrina Viola Kosti, Vasiliki Arg...