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167
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JMLR
2010
159views more  JMLR 2010»
15 years 1 months ago
Semi-Supervised Learning with Max-Margin Graph Cuts
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...
156
Voted
ICML
2009
IEEE
16 years 7 months ago
A simpler unified analysis of budget perceptrons
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Ilya Sutskever
190
Voted
ICALT
2007
IEEE
16 years 1 months ago
Designing Innovative Learning Activities Using Ubiquitous Computing
In this paper we present our pedagogical and technological approach for supporting the design of novel situated learning activities that can be conducted both, outside the school ...
Arianit Kurti, Marcelo Milrad, Daniel Spikol
148
Voted
ICANN
2007
Springer
16 years 1 months ago
Selection of Basis Functions Guided by the L2 Soft Margin
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
Ignacio Barrio, Enrique Romero, Lluís Belan...
ICASSP
2010
IEEE
15 years 5 months ago
Bayesian compressive sensing for phonetic classification
In this paper, we introduce a novel bayesian compressive sensing (CS) technique for phonetic classification. CS is often used to characterize a signal from a few support training...
Tara N. Sainath, Avishy Carmi, Dimitri Kanevsky, B...