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Akbar Siami Namin
Akbar Siami Namin
Professor of Computer Science, Texas Tech University
Verified email at ttu.edu - Homepage
Title
Cited by
Cited by
Year
A comparison of ARIMA and LSTM in forecasting time series
S Siami-Namini, N Tavakoli, AS Namin
2018 17th IEEE international conference on machine learning and applications …, 2018
13152018
The performance of LSTM and BiLSTM in forecasting time series
S Siami-Namini, N Tavakoli, AS Namin
2019 IEEE International conference on big data (Big Data), 3285-3292, 2019
11312019
Using mutation analysis for assessing and comparing testing coverage criteria
JH Andrews, LC Briand, Y Labiche, AS Namin
IEEE Transactions on Software Engineering 32 (8), 608-624, 2006
6482006
Forecasting economics and financial time series: ARIMA vs. LSTM
S Siami-Namini, AS Namin
arXiv preprint arXiv:1803.06386, 2018
3432018
Sufficient mutation operators for measuring test effectiveness
A Siami Namin, JH Andrews, DJ Murdoch
Proceedings of the 30th international conference on Software engineering …, 2008
2642008
The influence of size and coverage on test suite effectiveness
AS Namin, JH Andrews
Proceedings of the eighteenth international symposium on Software testing …, 2009
2052009
A comparative analysis of forecasting financial time series using arima, lstm, and bilstm
S Siami-Namini, N Tavakoli, AS Namin
arXiv preprint arXiv:1911.09512, 2019
1322019
Detecting phishing websites through deep reinforcement learning
M Chatterjee, AS Namin
2019 IEEE 43rd annual computer software and applications conference (COMPSAC …, 2019
1152019
Predicting vulnerable software components through n-gram analysis and statistical feature selection
Y Pang, X Xue, AS Namin
2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015
1082015
A survey on the moving target defense strategies: An architectural perspective
J Zheng, AS Namin
Journal of Computer Science and Technology 34, 207-233, 2019
1062019
The core cyber-defense knowledge, skills, and abilities that cybersecurity students should learn in school: Results from interviews with cybersecurity professionals
KS Jones, AS Namin, ME Armstrong
ACM Transactions on Computing Education (TOCE) 18 (3), 1-12, 2018
1002018
The use of mutation in testing experiments and its sensitivity to external threats
AS Namin, S Kakarla
Proceedings of the 2011 International Symposium on Software Testing and …, 2011
962011
Can machine/deep learning classifiers detect zero-day malware with high accuracy?
F Abri, S Siami-Namini, MA Khanghah, FM Soltani, AS Namin
2019 IEEE international conference on big data (Big Data), 3252-3259, 2019
662019
Forecasting economics and financial time series: ARIMA vs
S Siami-Namini, AS Namin
LSTM. arXiv 1803, 2018
662018
A survey of privacy concerns in wearable devices
P Datta, AS Namin, M Chatterjee
2018 IEEE international conference on big data (big data), 4549-4553, 2018
582018
Forecasting economic and financial time series: Arima vs. LSTM
SS Namin, AS Namin
arXiv preprint arXiv:1803.06386, 2018
582018
An autoencoder-based deep learning approach for clustering time series data
N Tavakoli, S Siami-Namini, M Adl Khanghah, F Mirza Soltani, ...
SN Applied Sciences 2, 1-25, 2020
542020
Finding sufficient mutation operators via variable reduction
AS Namin, JH Andrews
Second Workshop on Mutation Analysis (Mutation 2006-ISSRE Workshops 2006), 5-5, 2006
522006
Identifying effective test cases through k-means clustering for enhancing regression testing
Y Pang, X Xue, AS Namin
2013 12th International Conference on Machine Learning and Applications 2, 78-83, 2013
482013
Internet use and cybersecurity concerns of individuals with visual impairments
FA Inan, AS Namin, RL Pogrund, KS Jones
Journal of Educational Technology & Society 19 (1), 28-40, 2016
462016
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