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» Structured Sparsity in Structured Prediction
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NIPS
2007
15 years 5 months ago
Structured Learning with Approximate Inference
In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
Alex Kulesza, Fernando Pereira
ML
2002
ACM
163views Machine Learning» more  ML 2002»
15 years 3 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
NAR
2006
61views more  NAR 2006»
15 years 4 months ago
MAVL/StickWRLD: analyzing structural constraints using interpositional dependencies in biomolecular sequence alignments
The increasing availability of structurally aligned protein families has made it possible to use statistical methods to discover regions of interpositional dependenciesof residue ...
Hatice Gulcin Ozer, William C. Ray
HICSS
2005
IEEE
133views Biometrics» more  HICSS 2005»
15 years 9 months ago
Identifying Facilitators and Inhibitors of Market Structure Change: A Hybrid Theory of Unbiased Electronic Markets
The electronic markets hypothesis (EMH) in the information systems (IS) literature suggests that information technology (IT) will reduce coordination costs across firms, leading t...
Nelson F. Granados, Alok Gupta, Robert J. Kauffman
AAAI
2008
15 years 6 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes