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ICIP
2003
IEEE
16 years 2 months ago
Image compression with on-line and off-line learning
Images typically contain smooth regions, which are easily compressed by linear transforms, and high activity regions (edges, textures), which are harder to compress. To compress t...
Patrice Y. Simard, Christopher J. C. Burges, David...
IJCNN
2008
IEEE
15 years 6 months ago
Active Meta-Learning with Uncertainty Sampling and Outlier Detection
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
102
Voted
BMCBI
2010
165views more  BMCBI 2010»
15 years 16 days ago
MTar: a computational microRNA target prediction architecture for human transcriptome
Background: MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in importa...
Vinod Chandra, Reshmi Girijadevi, Achuthsankar S. ...
123
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PPOPP
2009
ACM
16 years 29 days ago
Mapping parallelism to multi-cores: a machine learning based approach
The efficient mapping of program parallelism to multi-core processors is highly dependent on the underlying architecture. This paper proposes a portable and automatic compiler-bas...
Zheng Wang, Michael F. P. O'Boyle
126
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AAAI
1996
15 years 1 months ago
Integrating Grid-Based and Topological Maps for Mobile Robot Navigation
Research on mobile robot navigation has produced two major paradigms for mapping indoorenvironments: grid-based and topological. While grid-based methods produce accurate metric m...
Sebastian Thrun, Arno Bücken