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» Sparse conformal predictors
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CGF
2008
101views more  CGF 2008»
13 years 5 months ago
Spectral Conformal Parameterization
We present a spectral approach to automatically and efficiently obtain discrete free-boundary conformal parameterizations of triangle mesh patches, without the common artifacts du...
Patrick Mullen, Yiying Tong, Pierre Alliez, Mathie...
JMLR
2010
154views more  JMLR 2010»
12 years 12 months ago
Infinite Predictor Subspace Models for Multitask Learning
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
Piyush Rai, Hal Daumé III
PC
2011
413views Management» more  PC 2011»
13 years 4 days ago
Exploiting thread-level parallelism in the iterative solution of sparse linear systems
We investigate the efficient iterative solution of large-scale sparse linear systems on shared-memory multiprocessors. Our parallel approach is based on a multilevel ILU precondit...
José Ignacio Aliaga, Matthias Bollhöfe...
JMLR
2010
110views more  JMLR 2010»
12 years 12 months ago
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net
A new approach to regression regularization called the Pairwise Elastic Net is proposed. Like the Elastic Net, it simultaneously performs automatic variable selection and continuo...
Alexander Lorbert, David Eis, Victoria Kostina, Da...
AAAI
2010
13 years 5 months ago
Multi-Task Sparse Discriminant Analysis (MtSDA) with Overlapping Categories
Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...
Yahong Han, Fei Wu, Jinzhu Jia, Yueting Zhuang, Bi...