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» Optimization of Machine Descriptions for Efficient Use
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ICML
2009
IEEE
14 years 10 months ago
Learning structural SVMs with latent variables
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...
Chun-Nam John Yu, Thorsten Joachims
ML
2008
ACM
13 years 9 months ago
Large margin vs. large volume in transductive learning
Abstract. We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis spa...
Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik
IPPS
2002
IEEE
14 years 2 months ago
Efficient Pipelining of Nested Loops: Unroll-and-Squash
The size and complexity of current custom VLSI have forced the use of high-level programming languages to describe hardware, and compiler and synthesis technology bstract designs ...
Darin Petkov, Randolph E. Harr, Saman P. Amarasing...
ICML
2007
IEEE
14 years 10 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
PPOPP
2009
ACM
14 years 9 months 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