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» Predicting relative performance of classifiers from samples
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PLDI
2003
ACM
14 years 28 days ago
Predicting whole-program locality through reuse distance analysis
Profiling can accurately analyze program behavior for select data inputs. We show that profiling can also predict program locality for inputs other than profiled ones. Here loc...
Chen Ding, Yutao Zhong
INFOCOM
2010
IEEE
13 years 6 months ago
Two Samples are Enough: Opportunistic Flow-level Latency Estimation using NetFlow
—The inherent support in routers (SNMP counters or NetFlow) is not sufficient to diagnose performance problems in IP networks, especially for flow-specific problems where the ...
Myungjin Lee, Nick G. Duffield, Ramana Rao Kompell...
KDD
2002
ACM
108views Data Mining» more  KDD 2002»
14 years 8 months ago
Incremental Machine Learning to Reduce Biochemistry Lab Costs in the Search for Drug Discovery
This paper promotes the use of supervised machine learning in laboratory settings where chemists have a large number of samples to test for some property, and are interested in id...
George Forman
MIR
2010
ACM
325views Multimedia» more  MIR 2010»
13 years 9 months ago
A classification-driven similarity matching framework for retrieval of biomedical images
This paper presents a classification-driven biomedical image retrieval system to bride the semantic gap by transforming image features to their global categories at different gran...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...
BMCBI
2007
154views more  BMCBI 2007»
13 years 7 months ago
Classification of heterogeneous microarray data by maximum entropy kernel
Background: There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are c...
Wataru Fujibuchi, Tsuyoshi Kato