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BMCBI
2007
207views more  BMCBI 2007»
14 years 12 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
ECCV
2010
Springer
15 years 9 hour ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
ICCV
2003
IEEE
16 years 1 months ago
Recognition of Group Activities using Dynamic Probabilistic Networks
Dynamic Probabilistic Networks (DPNs) are exploited for modelling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust...
Shaogang Gong, Tao Xiang
DCOSS
2008
Springer
15 years 1 months ago
LiveNet: Using Passive Monitoring to Reconstruct Sensor Network Dynamics
We describe LiveNet, a set of tools and analysis methods for reconstructing the complex behavior of a deployed sensor network. LiveNet is based on the use of multiple passive packe...
Bor-rong Chen, Geoffrey Peterson, Geoffrey Mainlan...
ADMA
2006
Springer
153views Data Mining» more  ADMA 2006»
15 years 1 months ago
An Effective Combination Based on Class-Wise Expertise of Diverse Classifiers for Predictive Toxicology Data Mining
This paper presents a study on the combination of different classifiers for toxicity prediction. Two combination operators for the Multiple-Classifier System definition are also pr...
Daniel Neagu, Gongde Guo, Shanshan Wang