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ASUNAM
2010
IEEE
13 years 9 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
ICPR
2004
IEEE
14 years 8 months ago
Visual Learning and Recognition of a Probabilistic Spatio-Temporal Model of Cyclic Human Locomotion
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
Miha Peternel, Ales Leonardis
ICML
2003
IEEE
14 years 8 months ago
Marginalized Kernels Between Labeled Graphs
A new kernel function between two labeled graphs is presented. Feature vectors are defined as the counts of label paths produced by random walks on graphs. The kernel computation ...
Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi
MOBICOM
2010
ACM
13 years 7 months ago
Did you see Bob?: human localization using mobile phones
Finding a person in a public place, such as in a library, conference hotel, or shopping mall, can be difficult. The difficulty arises from not knowing where the person may be at t...
Ionut Constandache, Xuan Bao, Martin Azizyan, Romi...
WWW
2008
ACM
14 years 8 months ago
Behavioral classification on the click graph
A bipartite query-URL graph, where an edge indicates that a document was clicked for a query, is a useful construct for finding groups of related queries and URLs. Here we use thi...
Martin Szummer, Nick Craswell