scholarly journals High-throughput fuzzy clustering on heterogeneous architectures

2020 ◽  
Vol 106 ◽  
pp. 401-411 ◽  
Author(s):  
Juan M. Cebrian ◽  
Baldomero Imbernón ◽  
Jesus Soto ◽  
José M. García ◽  
José M. Cecilia
Keyword(s):  
High Throughput ◽  
Fuzzy Clustering ◽  
Heterogeneous Architectures

scholarly journals High-throughput powder diffraction. IV. Cluster validation using silhouettes and fuzzy clustering

2004 ◽  
Vol 37 (6) ◽  
pp. 874-882 ◽  
Author(s):  
Gordon Barr ◽  
Wei Dong ◽  
Christopher J. Gilmore
Keyword(s):  
Powder Diffraction ◽  
High Throughput ◽  
Fuzzy Clustering ◽  
Correlation Matrix ◽  
Three Dimensional ◽  
Cluster Validation ◽  
Cluster Membership ◽  
Components Analysis ◽  
Diffraction Patterns ◽  
Classification Procedures

In two previous papers [Gilmore, Barr & Paisley (2004).J. Appl. Cryst.37, 231–242; Barr, Dong & Gilmore (2004).J. Appl. Cryst.37, 243–252], it was demonstrated how to generate a correlation matrix by comparing full powder diffraction patterns, and then partition the diffractograms into groups using multivariate statistics and associated classification procedures. For clustering the patterns into related sets, dendrograms, metric multidimensional scaling and three-dimensional principal-components analysis score plots are employed. However, sometimes cluster membership for certain patterns is not always very clear or other ambiguities may arise; this paper describes cluster validation techniques using silhouettes and fuzzy clustering. The two methods operate in a complementary way: in some cases silhouettes are the most useful, and in others fuzzy clustering is more applicable. These procedures are available as options in the commercial computer programPolySNAP.

High-Throughput Training of Deep CNNs on ReRAM-based Heterogeneous Architectures via Optimized Normalization Layers

2021 ◽  
pp. 1-1
Author(s):  
Biresh Kumar Joardar ◽  
Aryan Deshwal ◽  
Janardhan Rao Doppa ◽  
Partha Pratim Pande ◽  
Krishnendu Chakrabarty
Keyword(s):  
High Throughput ◽  
Heterogeneous Architectures

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction
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