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PAMI
2006
147views more  PAMI 2006»
14 years 9 months ago
Bayesian Gaussian Process Classification with the EM-EP Algorithm
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Hyun-Chul Kim, Zoubin Ghahramani
SC
1995
ACM
15 years 1 months ago
Distributing a Chemical Process Optimization Application Over a Gigabit Network
We evaluate the impact of a gigabit network on the implementation of a distributed chemical process optimization application. The optimization problem is formulated as a stochasti...
Robert L. Clay, Peter Steenkiste
ISNN
2005
Springer
15 years 3 months ago
Lidar Signal Processing for Under-Water Object Detection
Abstract. This paper presents Artificial Neural Network (ANN) based architecture for underwater object detection from Light Detection And Ranging (Lidar) data. Lidar gives a sequen...
Vikramjit Mitra, Chia-Jiu Wang, Satarupa Banerjee
NIPS
2007
14 years 11 months ago
Stability Bounds for Non-i.i.d. Processes
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
Mehryar Mohri, Afshin Rostamizadeh
JCP
2008
167views more  JCP 2008»
14 years 9 months ago
Accelerated Kernel CCA plus SVDD: A Three-stage Process for Improving Face Recognition
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Ming Li, Yuanhong Hao