Skip to main content
Statistics
STAT
Statistics
Study
Prospective Students
Current Students
Research
Research Areas
Research Groups
People
All People
Faculty
Affiliate Faculty
Instructional Faculty
Research Scientists
Research Staff
Postdoctoral Fellows
Administrative Staff
Alumni
Students
News
Events
History
Al-Kindi
Al-Kindi Distinguished Statistics Lectures
Al-Kindi Student Awards
About
CEMSE Division
Apply
processing
Faster prediction of wireless downtime
1 min read ·
Sat, Jul 2 2016
News
applied mathematics
computational science
signal
processing
Computer science
An efficient simulation scheme that hones in on the rarest elements in a dataset can help predict capacity exceedances in wireless networks.