Makan fardad.

Teaching. ELE 612/412. ELE 791. ELE 612/412 - Modern Control Systems - Spring 2024. Syllabus. Textbook. Lecture Notes. All lecture notes as one file. Homework & Solutions.This work proposes a progressive weight pruning approach based on ADMM (Alternating Direction Method of Multipliers), a powerful technique to deal with non-convex optimization problems with potentially combinatorial constraints. Motivated by dynamic programming, the proposed method reaches extremely high pruning rate by using partial …Makan Fardad Home CV : Research Publications Google Scholar Software : Teaching ELE 400 ELE 603 : ELE 603 - Functional Methods of Engineering Analysis - Fall 2023 ...Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li NeurIPS 2021. Revisit the strength of min-max optimization in the context of adversarial attack generation Reproduce Main Results. Please check neurips21 folder for reproducing the robust adversarial attack results presented in the paper.Rajdoot Tandoori – Manchester Indian Restaurant. Celebrating 52 years in Manchester. Book a table. Welcome to authentic, North Indian cuisine with a Nepalese twist in the …

R. Rajaram wishes to thank Umesh Vaidya and Makan Fardad for their suggestions in writing this article. Reprints and Permissions. Please note: We are unable to provide a copy of the article, please see our help page How do I view content?[20]M. Fardad and B. Bamieh, \A necessary and su cient frequency domain criterion for the passivity of SISO sampled-data systems," IEEE Transactions on Automatic Control, vol. 54, no. 3, pp. 611{614, 2009. [21]M. Fardad and B. Bamieh, \Perturbation methods in stability and norm analysis of spatiallyI am an unapologetic champion of serving a salad with Thanksgiving dinner. Even though I am completely here for the casseroles, a pile of raw leaves can cleanse the palate and invi...

Tianyun Zhang, Shaokai Ye, Yipeng Zhang, Yanzhi Wang, Makan Fardad. 12 Feb 2018 (modified: 12 Feb 2018) ICLR 2018 Workshop Submission Readers: Everyone. Abstract: We present a systematic weight pruning framework of deep neural networks (DNNs) using the alternating direction method of multipliers (ADMM).

Fu Lin, Makan Fardad, and Mihailo R. Jovanović Abstract— We design sparse and block sparse feedback gains that mini- mize the variance amplification (i.e., the norm) of distributed systems. College of Engineering and Computer Science at Syracuse ... Our team of research specialists bought and tested the best stick vacuums on the market to help you make a smart purchase. Expert Advice On Improving Your Home Videos Latest View A...Abstract. The worst-case training principle that minimizes the maximal adversarial loss, also known as adversarial training (AT), has shown to be a state-of-the-art approach for enhancing adversarial robustness. Nevertheless, min-max optimization beyond the purpose of AT has not been rigorously explored in the adversarial context. Makan Fardad. Associate Professor. Electrical Engineering and Computer Science. 3-189 CST. [email protected]. 315.443.4406. Personal Website. Degree (s): BSc in Electrical Engineering, Sharif University of Technology, Iran, 1998. MSc in Control Engineering, Iran University of Science and Technology, 2000.

/ Kearney, Griffin; Fardad, Makan. 2018 IEEE Conference on Decision and Control, CDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1821-1826 8619519 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December). Research output: Chapter in Book/Entry/Poem › Conference contribution

Adam-admm: A unified, systematic framework of structured weight pruning for dnns. Published in ArXiv, 2018. Recommended citation: Tianyun Zhang*, Kaiqi Zhang*, Shaokai Ye*, Jiayu Li, Jian Tang, Wujie Wen, Xue Lin, Makan Fardad, Yanzhi Wang Abstract

Optimization Based Data Enrichment Using Stochastic Dynamical System Models. Griffin M. Kearney, Makan Fardad. We develop a general framework for state estimation in systems modeled with noise-polluted continuous time dynamics and discrete time noisy measurements. Our approach is based on maximum likelihood estimation …The average speedups reach 3.15x and 8.52x when allowing a moderate accuracy loss of 2%. In this case, the model compression for convolutional layers is 15.0x, corresponding to 11.93x measured CPU speedup. As another example, for the ResNet-18 model on the CIFAR-10 data set, we achieve an unprecedented 54.2x structured pruning rate on …View Scopus Profile. Makan Fardad. Syracuse University, Department of Electrical Engineering & Computer Science. h-index. 2100. Citations. 22. h-index. 2001 2022. Research activity per year. Overview. Fingerprint. Network. Grants (10) Research output (82) Similar Profiles (1) Fingerprint. Dive into the research topics where Makan Fardad is active.M. Fardad is with the Department of Electrical Engineering and Computer Science, Syracuse University, New York 13244 (e-mail: [email protected]). of the algebraic Riccati equation A P+PA Q 2 = 0 with Toeplitz coefficients A;Q( d A= Q= 2) then P can be of the same order as N. Thus, based on the definition of almost Toeplitzness proposed by [1], …Sijia Liu Member, IEEE, Swarnendu Kar, Member, IEEE, Makan Fardad, Member, IEEE, and Pramod K. Varshney Fellow, IEEE Abstract—In this paper, we aim to design the optimal sen-sor collaboration strategy for the ... M. Fardad was supported by the National Science Foundation under awards EAGER ECCS-1545270 and CNS-1329885. prior to …Dads today are doing more than ever before. Dads, tell us what modern fatherhood looks like to you! What’s your defining moment as a dad? What do you do better than anyone? What’s ...

Makan Fardad, Associate Professor Ph.D., University of California, Santa Barbara, 2006 Comvex optimization; Design and optimal control of complex networks; Synchronization and consensus multi-agent systems. James W. Fawcett, Emeritus Teaching Professor Ph.D., Syracuse University, 1981 Software, software complexity, re-use, salvageMakan Fardad Optimal sparse network design in large-scale dynamical systems. Back to Active Faculty. 2-212 Center of Science & Technology Syracuse University Syracuse, NY 13244 315.443.1060. CASE is a NYSTAR-designated Center for Advanced Technology (CAT). SU CASE Resource Links ...This work proposes a progressive weight pruning approach based on ADMM (Alternating Direction Method of Multipliers), a powerful technique to deal with non-convex optimization problems with potentially combinatorial constraints. Motivated by dynamic programming, the proposed method reaches extremely high pruning rate by using partial …for example Fardad_ELE612_Hw1.pdf. Homework solutions will be posted on the class website or emailed soon after the deadline and late homework will not be accepted. While discussions on home-work problems are allowed, even encouraged, it is critical that assignments be completed individually and not as a team e ort.Makan Fardad; We propose a system theoretic approach to the identification and mitigation of vulnerabilities to cyber attacks, in networks of dynamical systems.

Authors. Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li. Abstract. The worst-case training principle that minimizes the maximal adversarial loss, also known as adversarial training (AT), has shown to be a state-of-the-art approach for enhancing adversarial robustness.

M. Fardad 1 MakanMMakanakan FFFardardardadadad Electrical Eng. & Computer Sci. Tel: (805) 280{1232 3-189 SciTech, Syracuse Univ. Email: [email protected] Deep neural networks (DNNs) although achieving human-level performance in many domains, have very large model size that hinders their broader applications on edge computing devices. Extensive research work have been conducted on DNN model compression or pruning. However, most of the previous work took heuristic approaches. This work proposes a progressive weight pruning approach based on ADMM ...Assistant Professor Makan Fardad is exposing minor failures in infrastructure networks to stop them from snowballing into full-blown catastrophes.Good morning, Quartz readers! Good morning, Quartz readers! Facebook faces an “international grand committee” of parliaments. The UK seized a number of internal Facebook documents ...Adam-admm: A unified, systematic framework of structured weight pruning for dnns. Published in ArXiv, 2018. Recommended citation: Tianyun Zhang*, Kaiqi Zhang*, Shaokai Ye*, Jiayu Li, Jian Tang, Wujie Wen, Xue Lin, Makan Fardad, Yanzhi Wang AbstractEpidermolysis bullosa (EB) is a group of disorders in which skin blisters form after a minor injury. It is passed down in families. Epidermolysis bullosa (EB) is a group of disorde...Authors. Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li. Abstract. The worst-case training principle that minimizes the maximal adversarial loss, also known as adversarial training (AT), has shown to be a state-of-the-art approach for enhancing adversarial robustness.College of Engineering & Computer Science 3-189 SciTech Syracuse University New York 13244 Tel: +1 (315) 443-4406 Fax: +1 (315) 443-4936 Makan Fardad (makan@syr) Mon 1:00pm--2:00pm Wed 1:00pm--2:00pm : 3-189 SciTech : Lecture Notes Lecture 1 (Mon, 13 Jan) Lecture 2 (Wed, 15 Jan) MLK Day (Mon, 20 Jan)

DOI: 10.1007/978-3-030-47426-3_22 Corpus ID: 218593867; SGCN: A Graph Sparsifier Based on Graph Convolutional Networks @article{Li2020SGCNAG, title={SGCN: A Graph Sparsifier Based on Graph Convolutional Networks}, author={Jiayu Li and Tianyun Zhang and Hao Tian and Shengmin Jin and Makan Fardad and Reza Zafarani}, …

[20]M. Fardad and B. Bamieh, \A necessary and su cient frequency domain criterion for the passivity of SISO sampled-data systems," IEEE Transactions on Automatic Control, vol. 54, no. 3, pp. 611{614, 2009. [21]M. Fardad and B. Bamieh, \Perturbation methods in stability and norm analysis of spatially

2011. Design of optimal sparse interconnection graphs for synchronization of oscillator networks. M Fardad, F Lin, MR Jovanović. IEEE Transactions on Automatic Control 59 (9), 2457-2462. , 2014. 101. 2014. Optimal periodic sensor scheduling in networks of dynamical systems. S Liu, M Fardad, E Masazade, PK Varshney.Makan Fardad Fardad has been a professor of electrical engineering in the Department of Electrical Engineering and Computer Science since 2008. Fardad is developing a mathematical framework that will expose the critical fragilities that exist within infrastructure networks, like the power grid, so they can be amended before causing large-scale ...Zhao, P, Xu, K, Zhang, T, Fardad, M, Wang, Y & Lin, X 2018, Reinforced adversarial attacks on deep neural networks using ADMM. in 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings., 8646651, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings, …Makan W Fardad lives in Fayetteville, NY. They have also lived in Ventura, CA and Syracuse, NY. Makan is related to Anna S Chernobai . View Makan's cell phone and current address. Makan W Fardad . Fayetteville, …Zhao, P, Xu, K, Zhang, T, Fardad, M, Wang, Y & Lin, X 2018, Reinforced adversarial attacks on deep neural networks using ADMM. in 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings., 8646651, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings, …Makan Fardad Pron.: Maa-'kaan Far-'dad Associate Professor Electrical Engineering & Computer Science : EECS | ECS | SU: Makan Fardad Home CV : Research … Specialties: Fardad Mobin, MD is a highly skilled, board-certified neurosurgeon with considerable experience in treating a number of spinal disorders. At his practice, Mobin Neurosurgery, Dr. Mobin is dedicated to the diagnosis, treatment, and care of patients in Beverly Hills, California, providing them with much-needed relief from spinal pain. With over 2,000 spinal surgeries under his belt ... Deep neural networks (DNNs) although achieving human-level performance in many domains, have very large model size that hinders their broader applications on edge computing devices. Extensive research work have been conducted on DNN model compression or pruning. However, most of the previous work took heuristic approaches. …[email protected] before the end of class. Furthermore, by mid-October students will be required to choose a research project, on which they will give an oral presentation (after Thanksgiving Break) and hand in a written report (due on the last day of classes). Students may work on their projects in groups of two, but it is crucial that both

Optimization Based Data Enrichment Using Stochastic Dynamical System Models. Griffin M. Kearney, Makan Fardad. We develop a general framework for state estimation in systems modeled with noise-polluted continuous time dynamics and discrete time noisy measurements. Our approach is based on maximum likelihood estimation …Li, J, Zhang, T, Tian, H, Jin, S, Fardad, M & Zafarani, R 2020, SGCN: A Graph Sparsifier Based on Graph Convolutional Networks. in HW Lauw, E-P Lim, RC-W Wong, A Ntoulas, S-K Ng & SJ Pan (eds), Advances in Knowledge Discovery and Data Mining - 24th Pacific-Asia Conference, PAKDD 2020, Proceedings. Lecture Notes in Computer Science …Tianyun Zhang, Shaokai Ye, Kaiqi Zhang, Jian Tang, Wujie Wen, Makan Fardad, Yanzhi Wang; Proceedings of the European Conference on Computer Vision (ECCV), 2018, pp. 184-199 Abstract Weight pruning methods for deep neural networks (DNNs) have been investigated recently, but prior work in this area is mainly heuristic, iterative pruning, …Poster Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang · Tianyun Zhang · Sijia Liu · Pin-Yu Chen · Jiacen Xu · Makan Fardad · Bo LiInstagram:https://instagram. fargo dispensary menucyber awareness challenge 2024 knowledge check answersisotopes baseball seating chartubs arena section 106 Fu Lin, Makan Fardad, Mihailo R. Jovanovic Department of Electrical Engineering & Computer Science Research output : Contribution to journal › Article › peer-review amanda hardy boxerwells funeral home mn Abstract. The worst-case training principle that minimizes the maximal adversarial loss, also known as adversarial training (AT), has shown to be a state-of-the-art approach for enhancing adversarial robustness. Nevertheless, min-max optimization beyond the purpose of AT has not been rigorously explored in the adversarial context. lcp vs glock 42 College of Engineering & Computer Science 3-189 SciTech Syracuse University New York 13244 Tel: +1 (315) 443-4406 Fax: +1 (315) 443-4936 Zhao, P, Xu, K, Zhang, T, Fardad, M, Wang, Y & Lin, X 2018, Reinforced adversarial attacks on deep neural networks using ADMM. in 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings., 8646651, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1169 ... "At some point, they will have to take in consideration unit economics and increase prices." Ola is replicating its tried and tested formula from its home country, India, in intern...