<--- Back to Details
First PageDocument Content
Computational complexity theory / Cybernetics / Formal sciences / Computer science / Best /  worst and average case / Stochastic / Algorithm / Control theory / Applied mathematics / Mathematics / Analysis of algorithms
Date: 2014-03-25 14:56:33
Computational complexity theory
Cybernetics
Formal sciences
Computer science
Best
worst and average case
Stochastic
Algorithm
Control theory
Applied mathematics
Mathematics
Analysis of algorithms

Project Summary The design and analysis of network algorithmics solutions is a rich area of research that has led to numerous successful deployments in commercial Internet routers and network monitoring appliances. In ge

Add to Reading List

Source URL: www.cc.gatech.edu

Download Document from Source Website

File Size: 40,51 KB

Share Document on Facebook

Similar Documents

SCAN 2018 Post-conference Proceedings Special Issue of Journal of Computational and Applied Mathematics Call for Papers Special Issue on the 18th International Symposium on Scientific Computing, Computer Arithmetic,

SCAN 2018 Post-conference Proceedings Special Issue of Journal of Computational and Applied Mathematics Call for Papers Special Issue on the 18th International Symposium on Scientific Computing, Computer Arithmetic,

DocID: 1xVSx - View Document

Performance Evaluation and Optimization Models for Processing Networks with Queue-Dependent Production Quantities by John S. Hollywood S.B. Applied Mathematics

Performance Evaluation and Optimization Models for Processing Networks with Queue-Dependent Production Quantities by John S. Hollywood S.B. Applied Mathematics

DocID: 1xVdz - View Document

Mixture Density Networks Christopher M. Bishop Neural Computing Research Group Dept. of Computer Science and Applied Mathematics Aston University

Mixture Density Networks Christopher M. Bishop Neural Computing Research Group Dept. of Computer Science and Applied Mathematics Aston University

DocID: 1xUJf - View Document

Mathematics_BS_Applied.pdf

Mathematics_BS_Applied.pdf

DocID: 1xTYO - View Document

A BOOTSTRAP INTERVAL ESTIMATOR FOR BAYES’ CLASSIFICATION ERROR Chad M. Hawes and Carey E. Priebe Johns Hopkins University Department of Applied Mathematics and Statistics Baltimore, MDABSTRACT

A BOOTSTRAP INTERVAL ESTIMATOR FOR BAYES’ CLASSIFICATION ERROR Chad M. Hawes and Carey E. Priebe Johns Hopkins University Department of Applied Mathematics and Statistics Baltimore, MDABSTRACT

DocID: 1vrMQ - View Document