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ICML
2007
IEEE
14 years 8 months ago
Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
Kai Ni, Lawrence Carin, David B. Dunson
VEE
2012
ACM
222views Virtualization» more  VEE 2012»
12 years 3 months ago
Unpicking the knot: teasing apart VM/application interdependencies
Flexible and efficient runtime design requires an understanding of the dependencies among the components internal to the runtime and those between the application and the runtime...
Yi Lin, Stephen M. Blackburn, Daniel Frampton
CORR
2007
Springer
202views Education» more  CORR 2007»
13 years 7 months ago
Designing a Virtual Manikin Animation Framework Aimed at Virtual Prototyping
: In the industry, numerous commercial packages provide tools to introduce, and analyse human behaviour in the product's environment (for maintenance, ergonomics...), thanks t...
Antoine Rennuit, Alain Micaelli, Claude Andriot, F...
DCC
2009
IEEE
14 years 8 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang
SIAMSC
2008
129views more  SIAMSC 2008»
13 years 7 months ago
Bottom-Up Construction and 2: 1 Balance Refinement of Linear Octrees in Parallel
Abstract. In this article, we propose new parallel algorithms for the construction and 2:1 balance refinement of large linear octrees on distributed memory machines. Such octrees a...
Hari Sundar, Rahul S. Sampath, George Biros