HSNMC
2004
Springer
13 years 10 months ago
2004
Springer
— In this paper, we present a solution to the general problem of flow control for both unicast and multicast IP networks. We formulate a convex optimization problem that can be ...
PIMRC
2008
IEEE
13 years 11 months ago
2008
IEEE
—We extend the existing network utility maximization (NUM) framework for wired networks to wireless sensor networks by formulating it in order to take into account interference a...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
CVPR
2010
IEEE
14 years 17 days ago
2010
IEEE
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
CVPR
2010
IEEE
14 years 1 months ago
2010
IEEE
It has been shown that the 3D shape of a deformable surface in an image can be recovered by establishing correspondences between that image and a reference one in which the shape ...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
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...
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
Mobile robots often rely upon systems that render sensor data and perceptual features into costs that can be used in a planner. The behavior that a designer wishes the planner to ...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
This paper suggests a method for multiclass learning with many classes by simultaneously learning shared characteristics common to the classes, and predictors for the classes in t...