Sciweavers

DSMML
2004
Springer
13 years 10 months ago
Extensions of the Informative Vector Machine
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
CAIP
2009
Springer
246views Image Analysis» more  CAIP 2009»
13 years 11 months ago
Human Age Estimation by Metric Learning for Regression Problems
Abstract. The estimation of human age from face images is an interesting problem in computer vision. We proposed a general distance metric learning scheme for regression problems, ...
Yangjing Long
IROS
2009
IEEE
155views Robotics» more  IROS 2009»
13 years 11 months ago
Active learning using mean shift optimization for robot grasping
— When children learn to grasp a new object, they often know several possible grasping points from observing a parent’s demonstration and subsequently learn better grasps by tr...
Oliver Kroemer, Renaud Detry, Justus H. Piater, Ja...
SDM
2009
SIAM
172views Data Mining» more  SDM 2009»
14 years 1 months ago
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach.
This paper is concerned with the task of travel-time prediction for an arbitrary origin-destination pair on a map. Unlike most of the existing studies, which focus only on a parti...
Sei Kato, Tsuyoshi Idé
ICML
2005
IEEE
14 years 5 months ago
Heteroscedastic Gaussian process regression
This paper presents an algorithm to estimate simultaneously both mean and variance of a non parametric regression problem. The key point is that we are able to estimate variance l...
Alexander J. Smola, Quoc V. Le, Stéphane Ca...
CVPR
2009
IEEE
14 years 11 months ago
Nonrigid Shape Recovery by Gaussian Process Regression
Most state-of-the-art nonrigid shape recovery methods usually use explicit deformable mesh models to regularize surface deformation and constrain the search space. These triangu...
Jianke Zhu, Michael R. Lyu, Steven C. H. Hoi