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» A discriminative model for semi-supervised learning
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104
Voted
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
16 years 1 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
110
Voted
WSOM
2009
Springer
15 years 7 months ago
Self-Organization of Tactile Receptive Fields: Exploring Their Textural Origin and Their Representational Properties
In our earlier work, we found that feature space induced by tactile receptive fields (TRFs) are better than that by visual receptive fields (VRFs) in texture boundary detection t...
Choonseog Park, Heeyoul Choi, Yoonsuck Choe
87
Voted
SIGIR
2010
ACM
15 years 4 months ago
Multilabel classification with meta-level features
Effective learning in multi-label classification (MLC) requires an ate level of abstraction for representing the relationship between each instance and multiple categories. Curren...
Siddharth Gopal, Yiming Yang
116
Voted
ECAI
2008
Springer
15 years 2 months ago
Intelligent adaptive monitoring for cardiac surveillance
Monitoring patients in intensive care units is a critical task. Simple condition detection is generally insufficient to diagnose a patient and may generate many false alarms to the...
Lucie Callens, Guy Carrault, Marie-Odile Cordier, ...
106
Voted
DATAMINE
2006
157views more  DATAMINE 2006»
15 years 20 days ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz