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» Normalization in Support Vector Machines
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ECML
2007
Springer
16 years 18 days ago
Statistical Debugging Using Latent Topic Models
Abstract. Statistical debugging uses machine learning to model program failures and help identify root causes of bugs. We approach this task using a novel Delta-Latent-Dirichlet-Al...
David Andrzejewski, Anne Mulhern, Ben Liblit, Xiao...
PDP
2005
IEEE
16 years 9 hour ago
Distributed Data Collection through Remote Probing in Windows Environments
Distributed Data Collector (DDC) is a framework to ease and automate repetitive executions of console applications (probes) over a set of LAN networked Windows personal computers....
Patrício Domingues, Paulo Marques, Lu&iacut...
BMCBI
2008
138views more  BMCBI 2008»
15 years 6 months ago
Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote ho
Background: Nonnegative matrix factorization (NMF) is a feature extraction method that has the property of intuitive part-based representation of the original features. This uniqu...
Inkyung Jung, Jaehyung Lee, Soo-Young Lee, Dongsup...
EMNLP
2004
15 years 7 months ago
Max-Margin Parsing
We present a novel discriminative approach to parsing inspired by the large-margin criterion underlying support vector machines. Our formulation uses a factorization analogous to ...
Ben Taskar, Dan Klein, Mike Collins, Daphne Koller...
EACL
2006
ACL Anthology
15 years 7 months ago
Making Tree Kernels Practical for Natural Language Learning
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
Alessandro Moschitti