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» Learning Classifiers from Semantically Heterogeneous Data
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INFOCOM
2000
IEEE
14 years 1 months ago
RMX: Reliable Multicast for Heterogeneous Networks
—Although IP Multicast is an effective network primitive for best-effort, large-scale, multi-point communication, many multicast applications such as shared whiteboards, multi-pl...
Yatin Chawathe, Steven McCanne, Eric A. Brewer
ICIP
2003
IEEE
14 years 10 months ago
Statistical learning for effective visual information retrieval
For effective retrieval of visual information, statistical learning plays a pivotal role. Statistical learning in such a context faces at least two major mathematical challenges: ...
Edward Y. Chang, Beitao Li, Gang Wu, Kingshy Goh
EMNLP
2007
13 years 10 months ago
LEDIR: An Unsupervised Algorithm for Learning Directionality of Inference Rules
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
Rahul Bhagat, Patrick Pantel, Eduard H. Hovy
BMCBI
2007
207views more  BMCBI 2007»
13 years 9 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...
JMLR
2010
136views more  JMLR 2010»
13 years 3 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby