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NECO
2002
100views more  NECO 2002»
15 years 6 months ago
Robust Regression with Asymmetric Heavy-Tail Noise Distributions
In the presence of a heavy-tail noise distribution, regression becomes much more di cult. Traditional robust regression methods assume that the noise distribution is symmetric and...
Ichiro Takeuchi, Yoshua Bengio, Takafumi Kanamori
PRL
2007
107views more  PRL 2007»
15 years 6 months ago
Robust SS watermarking with improved capacity
Robustness is a key attribute of spread spectrum (SS) watermarking scheme. It is significantly deteriorated if one tries to achieve high embedding rate keeping other parameters u...
Santi P. Maity, Malay K. Kundu, Tirtha S. Das
CORR
2011
Springer
161views Education» more  CORR 2011»
14 years 10 months ago
Doubly Robust Policy Evaluation and Learning
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Miroslav Dudík, John Langford, Lihong Li
ICDM
2007
IEEE
143views Data Mining» more  ICDM 2007»
16 years 1 months ago
Bit Sequences and Biclustering of Text Documents
We propose a new technique for clustering of text documents that relies on a biclustering structure constructed on terms and documents. Our approach makes use of a greedy algorith...
Selim Mimaroglu, Kuniaki Uehara
GFKL
2005
Springer
88views Data Mining» more  GFKL 2005»
16 years 8 days ago
The Partial Robust M-approach
The PLS approach is a widely used technique to estimate path models relating various blocks of variables measured from the same population. It is frequently applied in the social s...
Sven Serneels, Christophe Croux, Peter Filzmoser, ...