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» A Bayesian Approach to Tackling Hard Computational Problems
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ICCV
2007
IEEE
16 years 1 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...
CVPR
2008
IEEE
16 years 1 months ago
A discriminatively trained, multiscale, deformable part model
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
INFOCOM
2005
IEEE
15 years 4 months ago
On achieving optimal throughput with network coding
— With the constraints of network topologies and link capacities, achieving the optimal end-to-end throughput in data networks has been known as a fundamental but computationally...
Zongpeng Li, Baochun Li, Dan Jiang, Lap Chi Lau
VTS
2003
IEEE
115views Hardware» more  VTS 2003»
15 years 4 months ago
Fault Testing for Reversible Circuits
Irreversible computation necessarily results in energy dissipation due to information loss. While small in comparison to the power consumption of today’s VLSI circuits, if curre...
Ketan N. Patel, John P. Hayes, Igor L. Markov
AI
2003
Springer
15 years 4 months ago
Hybrid Randomised Neighbourhoods Improve Stochastic Local Search for DNA Code Design
Sets of DNA strands that satisfy combinatorial constraints play an important role in various approaches to biomolecular computation, nanostructure design, and molecular tagging. Th...
Dan C. Tulpan, Holger H. Hoos