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» Learning to learn with the informative vector machine
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ICML
2008
IEEE
16 years 5 months ago
Learning to learn implicit queries from gaze patterns
In the absence of explicit queries, an alternative is to try to infer users' interests from implicit feedback signals, such as clickstreams or eye tracking. The interests, fo...
Antti Ajanki, Kai Puolamäki, Samuel Kaski
DAGM
2004
Springer
15 years 10 months ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf
TNN
2010
143views Management» more  TNN 2010»
14 years 11 months ago
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
ICML
2008
IEEE
16 years 5 months ago
Learning all optimal policies with multiple criteria
We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal policies for all linear pref...
Leon Barrett, Srini Narayanan
ICANN
2009
Springer
15 years 9 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola