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» Boosting Kernel Models for Regression
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SASP
2009
IEEE
291views Hardware» more  SASP 2009»
15 years 4 months ago
FCUDA: Enabling efficient compilation of CUDA kernels onto FPGAs
— As growing power dissipation and thermal effects disrupted the rising clock frequency trend and threatened to annul Moore’s law, the computing industry has switched its route...
Alexandros Papakonstantinou, Karthik Gururaj, John...
FDL
2003
IEEE
15 years 3 months ago
Synchronization of analogue and digital solvers in mixed-signal simulation on a SystemC platform
This contribution proposes a synchronization technique for solvers able to handle analogue extensions to SystemC, for modelling of general, mixed-mode systems with digital and non...
Tom J. Kazmierski, Hessa Al-Junaid
ICASSP
2009
IEEE
15 years 4 months ago
Data-driven online variational filtering in wireless sensor networks
In this paper, a data-driven extension of the variational algorithm is proposed. Based on a few selected sensors, target tracking is performed distributively without any informati...
Hichem Snoussi, Jean-Yves Tourneret, Petar M. Djur...
CVPR
2012
IEEE
13 years 9 days ago
Supervised hashing with kernels
Recent years have witnessed the growing popularity of hashing in large-scale vision problems. It has been shown that the hashing quality could be boosted by leveraging supervised ...
Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, Shi...
ICML
2009
IEEE
15 years 10 months ago
Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
Linli Xu, Martha White, Dale Schuurmans