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BMCBI
2010
139views more  BMCBI 2010»
13 years 8 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
ICML
2006
IEEE
14 years 9 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
ICASSP
2011
IEEE
13 years 14 days ago
Langevin and hessian with fisher approximation stochastic sampling for parameter estimation of structured covariance
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
Cornelia Vacar, Jean-François Giovannelli, ...
IEEEPACT
2005
IEEE
14 years 2 months ago
A Simple Divide-and-Conquer Approach for Neural-Class Branch Prediction
The continual demand for greater performance and growing concerns about the power consumption in highperformance microprocessors make the branch predictor a critical component of ...
Gabriel H. Loh
EWSN
2011
Springer
13 years 6 days ago
An Adaptive Algorithm for Compressive Approximation of Trajectory (AACAT) for Delay Tolerant Networks
Highly efficient compression provides a promising approach to address the transmission and computation challenges imposed by moving object tracking applications on resource constra...
Rajib Kumar Rana, Wen Hu, Tim Wark, Chun Tung Chou