7 search results - page 1 / 2 » A Unified Loss Function in Bayesian Framework for Support Ve... |
ICML
2001
IEEE
14 years 5 months ago
2001
IEEE
In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the d...
ALT
2000
Springer
14 years 1 months ago
2000
Springer
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...
ACCV
2010
Springer
12 years 11 months ago
2010
Springer
Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structu...
ML
2002
ACM
13 years 4 months ago
2002
ACM
In this paper, we elaborate on the well-known relationship between Gaussian Processes (GP) and Support Vector Machines (SVM) under some convex assumptions for the loss functions. ...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem...