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162
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JMLR
2008
230views more  JMLR 2008»
15 years 2 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
145
Voted
JMLR
2008
168views more  JMLR 2008»
15 years 2 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
JMLR
2008
151views more  JMLR 2008»
15 years 2 months ago
Learning to Combine Motor Primitives Via Greedy Additive Regression
The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
Manu Chhabra, Robert A. Jacobs
110
Voted
CSDA
2007
105views more  CSDA 2007»
15 years 2 months ago
Model selection for support vector machines via uniform design
The problem of choosing a good parameter setting for a better generalization performance in a learning task is the so-called model selection. A nested uniform design (UD) methodol...
Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin, S...
112
Voted
JNCA
2008
86views more  JNCA 2008»
15 years 2 months ago
Performance comparisons of load balancing algorithms for I/O-intensive workloads on clusters
Load balancing techniques play a critically important role in developing high-performance cluster computing platforms. Existing load balancing approaches are concerned with the ef...
Xiao Qin
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