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JMLR
2010
152views more  JMLR 2010»
15 years 1 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
JMLR
2010
145views more  JMLR 2010»
15 years 1 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
TSE
2010
102views more  TSE 2010»
15 years 1 months ago
Understanding Exception Handling: Viewpoints of Novices and Experts
Several recent studies indicate that many industrial applications exhibit poor quality in the design of exception-handling. To improve the quality of error-handling, we need to und...
Hina Shah, Carsten Görg, Mary Jean Harrold
ICASSP
2011
IEEE
14 years 10 months ago
Multiple speaker tracking using a microphone array by combining auditory processing and a gaussian mixture cardinalized probabil
Tracking speakers is an important application in smart environments. Acoustic tracking using microphone arrays is a challenging task due to two major reasons: On the one hand, mul...
Axel Plinge, Daniel Hauschildt, Marius H. Hennecke...
ICDE
2011
IEEE
269views Database» more  ICDE 2011»
14 years 10 months ago
Hyracks: A flexible and extensible foundation for data-intensive computing
Abstract—Hyracks is a new partitioned-parallel software platform designed to run data-intensive computations on large shared-nothing clusters of computers. Hyracks allows users t...
Vinayak R. Borkar, Michael J. Carey, Raman Grover,...