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» Structural Complexity of AvgBPP
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NIPS
2000
15 years 5 months ago
Discovering Hidden Variables: A Structure-Based Approach
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...
ISMB
1993
15 years 5 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
15 years 2 months ago
Large-Scale Support Vector Learning with Structural Kernels
Abstract. In this paper, we present an extensive study of the cuttingplane algorithm (CPA) applied to structural kernels for advanced text classification on large datasets. In par...
Aliaksei Severyn, Alessandro Moschitti
HIPC
2009
Springer
15 years 2 months ago
Extracting the textual and temporal structure of supercomputing logs
Supercomputers are prone to frequent faults that adversely affect their performance, reliability and functionality. System logs collected on these systems are a valuable resource o...
Sourabh Jain, Inderpreet Singh, Abhishek Chandra, ...
CVPR
2011
IEEE
15 years 19 days ago
Multi-agent event recognition in structured scenarios
We present a framework for the automatic recognition of complex multi-agent events in settings where structure is imposed by rules that agents must follow while performing activit...
Vlad Morariu, Larry Davis