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» Learning from Multiple Sources of Inaccurate Data
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CORR
2007
Springer
164views Education» more  CORR 2007»
13 years 7 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach
KDD
1998
ACM
190views Data Mining» more  KDD 1998»
13 years 11 months ago
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
R. Bharat Rao, Scott Rickard, Frans Coetzee
ACL
1996
13 years 8 months ago
Integrating Multiple Knowledge Sources to Disambiguate Word Sense: An Exemplar-Based Approach
In this paper, we present a new approach for word sense disambiguation (WSD) using an exemplar-based learning algorithm. This approach integrates a diverse set of knowledge source...
Hwee Tou Ng, Hian Beng Lee
ECML
2004
Springer
14 years 26 days ago
SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
Rong Jin, Huan Liu
ML
2010
ACM
181views Machine Learning» more  ML 2010»
13 years 5 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor