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» Generalizing by Removing Detail
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138
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IDA
2007
Springer
15 years 3 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
123
Voted
COMPGEOM
2009
ACM
15 years 10 months ago
Randomly removing g handles at once
It was shown in [11] that any orientable graph of genus g can be probabilistically embedded into a graph of genus g − 1 with constant distortion. Removing handles one by one giv...
Glencora Borradaile, James R. Lee, Anastasios Sidi...
135
Voted
SEMCO
2009
IEEE
15 years 10 months ago
LAIR: A Language for Automated Semantics-Aware Text Sanitization Based on Frame Semantics
—We present LAIR: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and re...
Steffen Hedegaard, Søren Houen, Jakob Grue ...
IDA
2009
Springer
15 years 10 months ago
Iterative Subspace Decomposition for Ocular Artifact Removal from EEG Recordings
In this study, we present a method to remove ocular artifacts from electroencephalographic (EEG) recordings. This method is based on the detection of the EOG activation periods fro...
Cédric Gouy-Pailler, Reza Sameni, Marco Con...
132
Voted
CORR
2012
Springer
210views Education» more  CORR 2012»
13 years 11 months ago
Topological phase transition in a network model with preferential attachment and node removal
Preferential attachment is a popular model of growing networks. We consider a generalized model with random node removal, and a combination of preferential and random attachment. U...
Heiko Bauke, Cristopher Moore, Jean-Baptiste Rouqu...