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» Sublinear Optimization for Machine Learning
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JMLR
2008
209views more  JMLR 2008»
15 years 2 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 2 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
EMNLP
2008
15 years 3 months ago
Phrase Translation Probabilities with ITG Priors and Smoothing as Learning Objective
The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heurist...
Markos Mylonakis, Khalil Sima'an
107
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IJCNN
2000
IEEE
15 years 6 months ago
Continuous Optimization of Hyper-Parameters
Many machine learning algorithms can be formulated as the minimization of a training criterion which involves (1) \training errors" on each training example and (2) some hype...
Yoshua Bengio
DIS
2006
Springer
15 years 6 months ago
Optimal Bayesian 2D-Discretization for Variable Ranking in Regression
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Marc Boullé, Carine Hue