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» Obtaining Best Parameter Values for Accurate Classification
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NIPS
2004
13 years 9 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
ICRA
2009
IEEE
143views Robotics» more  ICRA 2009»
14 years 2 months ago
Revisiting uncertainty analysis for optimum planes extracted from 3D range sensor point-clouds
—In this work, we utilize a recently studied more accurate range noise model for 3D sensors to derive from scratch the expressions for the optimum plane which best fits a point-...
Kaustubh Pathak, Narunas Vaskevicius, Andreas Birk...
ICISP
2010
Springer
13 years 9 months ago
Selecting Optimal Orientations of Gabor Wavelet Filters for Facial Image Analysis
Abstract. Gabor wavelet-based methods have been widely used to extract representative features for face analysis. However, the existing methods usually suffer from high computation...
Tianqi Zhang, Bao-Liang Lu
ISQED
2006
IEEE
106views Hardware» more  ISQED 2006»
14 years 1 months ago
Parameterizable Architecture-Level SRAM Power Model Using Circuit-Simulation Backend for Leakage Calibration
We propose an accurate architecture-level power estimation method for SRAM memories. This hybrid method is composed of an analytical part for dynamic power estimation and a circui...
Minh Quang Do, Mindaugas Drazdziulis, Per Larsson-...
IJCNN
2007
IEEE
14 years 2 months ago
Evaluation of Performance Measures for SVR Hyperparameter Selection
— To obtain accurate modeling results, it is of primal importance to find optimal values for the hyperparameters in the Support Vector Regression (SVR) model. In general, we sea...
Koen Smets, Brigitte Verdonk, Elsa Jordaan