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ML
2006
ACM
121views Machine Learning» more  ML 2006»
15 years 7 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
PLDI
2003
ACM
16 years 26 days ago
Meta optimization: improving compiler heuristics with machine learning
Compiler writers have crafted many heuristics over the years to approximately solve NP-hard problems efficiently. Finding a heuristic that performs well on a broad range of applic...
Mark Stephenson, Saman P. Amarasinghe, Martin C. M...
349
Voted
RECOMB
2011
Springer
14 years 10 months ago
Rich Parameterization Improves RNA Structure Prediction
Motivation. Current approaches to RNA structure prediction range from physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, to machin...
Shay Zakov, Yoav Goldberg, Michael Elhadad, Michal...
ICPR
2002
IEEE
16 years 8 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...
ISWC
2006
IEEE
16 years 1 months ago
Discovering Characteristic Actions from On-Body Sensor Data
We present an approach to activity discovery, the unsupervised identification and modeling of human actions embedded in a larger sensor stream. Activity discovery can be seen as ...
David Minnen, Thad Starner, Irfan A. Essa, Charles...