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» Using Machine Learning to Focus Iterative Optimization
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IJCNLP
2005
Springer
15 years 8 months ago
PP-Attachment Disambiguation Boosted by a Gigantic Volume of Unambiguous Examples
We present a PP-attachment disambiguation method based on a gigantic volume of unambiguous examples extracted from raw corpus. The unambiguous examples are utilized to acquire prec...
Daisuke Kawahara, Sadao Kurohashi

Lab
652views
17 years 2 months ago
Electronic Enterprises Laboratory
Our research is motivated by a strong conviction that business processes in electronic enterprises can be designed to deliver high levels of performance through the use of mathemat...
GECCO
2004
Springer
127views Optimization» more  GECCO 2004»
15 years 8 months ago
Improved Niching and Encoding Strategies for Clustering Noisy Data Sets
Clustering is crucial to many applications in pattern recognition, data mining, and machine learning. Evolutionary techniques have been used with success in clustering, but most su...
Olfa Nasraoui, Elizabeth Leon
ICML
2009
IEEE
16 years 4 months ago
A majorization-minimization algorithm for (multiple) hyperparameter learning
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
ICML
2007
IEEE
16 years 4 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...