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ICML
2010
IEEE
15 years 5 months ago
From Transformation-Based Dimensionality Reduction to Feature Selection
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy
EOR
2010
87views more  EOR 2010»
15 years 4 months ago
Inventory systems with stochastic demand and supply: Properties and approximations
ic copy available at: http://ssrn.com/abstract=1115410 Inventory Systems with Stochastic Demand and Supply: Properties and Approximations Amanda J. Schmitt Center for Transportatio...
Amanda J. Schmitt, Lawrence V. Snyder, Zuo-Jun Max...
SIAMCO
2008
121views more  SIAMCO 2008»
15 years 4 months ago
A Direct Solution Method for Stochastic Impulse Control Problems of One-dimensional Diffusions
We consider stochastic impulse control problems where the process is driven by one-dimensional diffusions. Impulse control problems are widely applied to financial engineering and...
Masahiko Egami
JC
2007
94views more  JC 2007»
15 years 4 months ago
On the complexity of the multivariate Sturm-Liouville eigenvalue problem
We study the complexity of approximating the smallest eigenvalue of −∆ + q with Dirichlet boundary conditions on the d-dimensional unit cube. Here ∆ is the Laplacian, and th...
A. Papageorgiou
SDM
2010
SIAM
168views Data Mining» more  SDM 2010»
15 years 2 months ago
Convex Principal Feature Selection
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, J...