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ICDAR
2009
IEEE
15 years 9 months ago
Fast Incremental Learning Strategy Driven by Confusion Reject for Online Handwriting Recognition
In this paper, we present a new incremental learning strategy for handwritten character recognition systems. This learning strategy enables the recognition system to learn “rapi...
Abdullah Almaksour, Éric Anquetil
CICLING
2009
Springer
15 years 9 months ago
Semi-supervised Word Sense Disambiguation Using the Web as Corpus
Abstract. As any other classification task, Word Sense Disambiguation requires a large number of training examples. These examples, which are easily obtained for most of the tasks,...
Rafael Guzmán-Cabrera, Paolo Rosso, Manuel ...
STOC
1993
ACM
117views Algorithms» more  STOC 1993»
15 years 6 months ago
Efficient noise-tolerant learning from statistical queries
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Michael J. Kearns
ICDE
2006
IEEE
95views Database» more  ICDE 2006»
16 years 3 months ago
Learning from Aggregate Views
In this paper, we introduce a new class of data mining problems called learning from aggregate views. In contrast to the traditional problem of learning from a single table of tra...
Bee-Chung Chen, Lei Chen 0003, Raghu Ramakrishnan,...
ICANN
2009
Springer
15 years 7 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