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» Using Gaussian Processes to Optimize Expensive Functions
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NIPS
2008
13 years 9 months ago
Automatic online tuning for fast Gaussian summation
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed to...
Vlad I. Morariu, Balaji Vasan Srinivasan, Vikas C....
GLOBECOM
2006
IEEE
14 years 1 months ago
Feedback Capacity of Stationary Sources over Gaussian Intersymbol Interference Channels
Abstract— We consider discrete-time channels with finitelength intersymbol interference and additive Gaussian noise. The channel noise is considered to be a stationary ARMA (aut...
Shaohua Yang, Aleksandar Kavcic, Sekhar Tatikonda
CORR
2006
Springer
86views Education» more  CORR 2006»
13 years 7 months ago
Optimal Distortion-Power Tradeoffs in Sensor Networks: Gauss-Markov Random Processes
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements ...
Nan Liu, Sennur Ulukus
NIPS
2007
13 years 9 months ago
Selecting Observations against Adversarial Objectives
In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well...
Andreas Krause, H. Brendan McMahan, Carlos Guestri...
ICIP
2007
IEEE
14 years 9 months ago
High Dimension Lattice Vector Quantizer Design for Generalized Gaussian Distributions
LVQ is a simple but powerful tool for vector quantization and can be viewed as a vector generalization of uniform scalar quantization. Like VQ, LVQ is able to take into account sp...
Leonardo H. Fonteles, Marc Antonini