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» Ensemble Learning Based on Multi-Task Class Labels
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PR
2007
146views more  PR 2007»
14 years 11 months ago
ML-KNN: A lazy learning approach to multi-label learning
Abstract: Multi-label learning originated from the investigation of text categorization problem, where each document may belong to several predefined topics simultaneously. In mul...
Min-Ling Zhang, Zhi-Hua Zhou
NIPS
2007
15 years 1 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
79
Voted
IJNS
2007
133views more  IJNS 2007»
14 years 11 months ago
Online Learning of Objects in a Biologically Motivated Visual Architecture
We present a biologically motivated architecture for object recognition that is capable of online learning of several objects based on interaction with a human teacher. The system...
Heiko Wersing, Stephan Kirstein, Michael Gött...
126
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ICCV
2011
IEEE
13 years 11 months ago
Fisher Discrimination Dictionary Learning for Sparse Representation
Sparse representation based classification has led to interesting image recognition results, while the dictionary used for sparse coding plays a key role in it. This paper present...
Meng Yang, Lei Zhang, Xiangchu Feng, David Zhang
MCS
2004
Springer
15 years 5 months ago
Learn++.MT: A New Approach to Incremental Learning
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar