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SIAMIS
2010
152views more  SIAMIS 2010»
10 years 8 months ago
Nonparametric Regression between General Riemannian Manifolds
We study nonparametric regression between Riemannian manifolds based on regularized empirical risk minimization. Regularization functionals for mappings between manifolds should re...
Florian Steinke, Matthias Hein, Bernhard Schö...
JMLR
2010
161views more  JMLR 2010»
10 years 8 months ago
Empirical Bernstein Boosting
Concentration inequalities that incorporate variance information (such as Bernstein's or Bennett's inequality) are often significantly tighter than counterparts (such as...
Pannagadatta K. Shivaswamy, Tony Jebara
CORR
2010
Springer
114views Education» more  CORR 2010»
11 years 1 months ago
On the Stability of Empirical Risk Minimization in the Presence of Multiple Risk Minimizers
Abstract--Recently Kutin and Niyogi investigated several notions of algorithmic stability--a property of a learning map conceptually similar to continuity--showing that training-st...
Benjamin I. P. Rubinstein, Aleksandr Simma
ICASSP
2010
IEEE
11 years 1 months ago
Empirical quantization for sparse sampling systems
We propose a quantization design technique (estimator) suitable for new compressed sensing sampling systems whose ultimate goal is classiļ¬cation or detection. The design is base...
Michael A. Lexa
NIPS
2007
11 years 2 months ago
Learning Bounds for Domain Adaptation
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
NIPS
2008
11 years 2 months ago
Overlaying classifiers: a practical approach for optimal ranking
ROC curves are one of the most widely used displays to evaluate performance of scoring functions. In the paper, we propose a statistical method for directly optimizing the ROC cur...
Stéphan Clémençon, Nicolas Va...
ICML
2004
IEEE
12 years 2 months ago
Decentralized detection and classification using kernel methods
We consider the problem of decentralized detection under constraints on the number of bits that can be transmitted by each sensor. In contrast to most previous work, in which the ...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
ICML
2009
IEEE
12 years 2 months ago
Group lasso with overlap and graph lasso
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is ty...
Laurent Jacob, Guillaume Obozinski, Jean-Philippe ...
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