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EMNLP
2011
14 years 3 months ago
Class Label Enhancement via Related Instances
Class-instance label propagation algorithms have been successfully used to fuse information from multiple sources in order to enrich a set of unlabeled instances with class labels...
Zornitsa Kozareva, Konstantin Voevodski, Shang-Hua...
ICML
2002
IEEE
16 years 5 months ago
Combining Labeled and Unlabeled Data for MultiClass Text Categorization
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
Rayid Ghani
MOBIHOC
2004
ACM
16 years 3 months ago
Using labeled paths for loop-free on-demand routing in ad hoc networks
We present the Feasible Label Routing (FLR) protocol for mobile ad hoc networks, which uses path information to establish routes to destinations on demand. FLR enables loopfree in...
Hari Rangarajan, J. J. Garcia-Luna-Aceves
142
Voted
AAAI
2006
15 years 5 months ago
An Efficient Algorithm for Local Distance Metric Learning
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu
133
Voted
ASUNAM
2010
IEEE
15 years 5 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen