922 search results - page 14 / 185 » Learning Gaussian Process Models from Uncertain Data |
160
click to vote
Book
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
100
Voted
UAI
2000
15 years 29 days ago
2000
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...
104
click to vote
ICML
2010
IEEE
15 years 21 days ago
2010
IEEE
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
90
Voted
ICML
2005
IEEE
16 years 13 days ago
2005
IEEE
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
IJCAI
2003
15 years 1 months ago
2003
Multi-level spatial aggregates are important for data mining in a variety of scientific and engineering applications, from analysis of weather data (aggregating temperature and p...