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» Spectral Algorithms for Supervised Learning
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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
CVPR
2010
IEEE
15 years 5 months ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...
GLOBECOM
2007
IEEE
15 years 4 months ago
Minimizing Distribution Cost of Distributed Neural Networks in Wireless Sensor Networks
Abstract—This paper presents a novel study on how to distribute neural networks in a wireless sensor networks (WSNs) such that the energy consumption is minimized while improving...
Peng Guan, Xiaolin Li
IJCAI
2007
14 years 11 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans
ACL
2012
13 years 4 days ago
Selective Sharing for Multilingual Dependency Parsing
We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation i...
Tahira Naseem, Regina Barzilay, Amir Globerson