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ICML
2005
IEEE
16 years 21 days ago
Preference learning with Gaussian processes
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
Wei Chu, Zoubin Ghahramani
ICML
2005
IEEE
16 years 21 days ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
ICML
2003
IEEE
16 years 21 days ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky
GLOBECOM
2007
IEEE
15 years 6 months ago
Gaussian Approximations for Carrier Sense Modeling in Wireless Ad Hoc Networks
— Physical carrier sense for wireless multihop networks has attracted a certain degree of attention since it is a simple yet important mechanism for distributed channel access. S...
Francesco Rossetto, Michele Zorzi
ICC
2007
IEEE
15 years 6 months ago
A Low-Complexity Impulse Radio Receiver based upon Gaussian Mixtures
Abstract— Ultra wide band (UWB) impulse radio (IR) technology calls for robust and low-complexity receiver techniques. State-of-the-art proposals are both coherent ML receivers, ...
Tomaso Erseghe