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» Robust ranking models via risk-sensitive optimization
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CVPR
2008
IEEE
16 years 5 months ago
Face alignment via boosted ranking model
Face alignment seeks to deform a face model to match it with the features of the image of a face by optimizing an appropriate cost function. We propose a new face model that is al...
Gianfranco Doretto, Hao Wu, Xiaoming Liu 0002
CSDA
2007
136views more  CSDA 2007»
15 years 3 months ago
A note on iterative marginal optimization: a simple algorithm for maximum rank correlation estimation
The maximum rank correlation (MRC) estimator was originally studied by Han [1987. Nonparametric analysis of a generalized regression model. J. Econometrics 35, 303–316] and Sher...
Hansheng Wang
118
Voted
CVPR
2007
IEEE
16 years 5 months ago
Autocalibration via Rank-Constrained Estimation of the Absolute Quadric
We present an autocalibration algorithm for upgrading a projective reconstruction to a metric reconstruction by estimating the absolute dual quadric. The algorithm enforces the ra...
Manmohan Krishna Chandraker, Sameer Agarwal, Fredr...
124
Voted
CIKM
2009
Springer
15 years 10 months ago
Reducing the risk of query expansion via robust constrained optimization
We introduce a new theoretical derivation, evaluation methods, and extensive empirical analysis for an automatic query expansion framework in which model estimation is cast as a r...
Kevyn Collins-Thompson
NPL
2002
168views more  NPL 2002»
15 years 3 months ago
Reduced Rank Kernel Ridge Regression
Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...
Gavin C. Cawley, Nicola L. C. Talbot