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» Ensemble Learning Based on Multi-Task Class Labels
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PR
2007
146views more  PR 2007»
13 years 6 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
13 years 8 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
IJNS
2007
133views more  IJNS 2007»
13 years 7 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...
ICCV
2011
IEEE
12 years 7 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
14 years 22 days 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