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Fingerprint Dive into the research topics where Makan Fardad is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Sensors Engineering & Materials Science
Time varying systems Engineering & Materials Science
Controllers Engineering & Materials Science
Feedback Engineering & Materials Science
Method of multipliers Mathematics
Telecommunication links Engineering & Materials Science
Alternating Direction Method Mathematics
Topology Engineering & Materials Science

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Projects 2009 2023

Research Output 2001 2019

  • 1285 Citations
  • 18 h-Index
  • 46 Conference contribution
  • 23 Article

On the Induction of Cascading Failures in Transportation Networks

Kearney, G. & Fardad, M., Jan 18 2019, 2018 IEEE Conference on Decision and Control, CDC 2018. Institute of Electrical and Electronics Engineers Inc., p. 1821-1826 6 p. 8619519. (Proceedings of the IEEE Conference on Decision and Control; vol. 2018-December).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Cascading Failure
Transportation Networks
Proof by induction
Traffic Network
Cell
1 Citation (Scopus)

Reinforced adversarial attacks on deep neural networks using ADMM

Zhao, P., Xu, K., Zhang, T., Fardad, M., Wang, Y. & Lin, X., Feb 20 2019, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 1169-1173 5 p. 8646651. (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Distillation
Deep neural networks
Deep learning
3 Citations (Scopus)

A Memristor-Based Optimization Framework for Artificial Intelligence Applications

Liu, S., Wang, Y., Fardad, M. & Varshney, P. K., Jan 1 2018, In : IEEE Circuits and Systems Magazine. 18, 1, p. 29-44 16 p., 8288635.

Research output: Contribution to journalArticle

Memristors
Artificial intelligence
Linear equations
Learning systems
Quadratic programming

A systematic DNN weight pruning framework using alternating direction method of multipliers

Zhang, T., Ye, S., Zhang, K., Tang, J., Wen, W., Fardad, M. & Wang, Y., Jan 1 2018, Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. Ferrari, V., Sminchisescu, C., Weiss, Y. & Hebert, M. (eds.). Springer Verlag, p. 191-207 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11212 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Method of multipliers
Alternating Direction Method
Pruning
Neural Networks
Nonconvex Optimization
1 Citation (Scopus)

On a linear programming approach to the optimal seeding of cascading failures

Fardad, M. & Kearney, G., Jan 18 2018, 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-January. p. 102-107 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Cascading Failure
Linear programming
Convex optimization
Cascade
System theory