Makan fardad.
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 …
We consider the design of optimal state feedback gains subject to structural constraints on the distributed controllers. These constraints are in the form of sparsity requirements for the feedback matrix, implying that each controller has access to information from only a limited number of subsystems. The minimizer of this constrained optimal control problem …: Get the latest CSC Financial stock price and detailed information including news, historical charts and realtime prices. Indices Commodities Currencies StocksMakan Fardad received the B.S. and M.S. degrees in electrical engineering from Sharif University of Technology and Iran University of Science and Technology, respectively. He received the Ph.D. degree in mechanical engineering from the University of California, Santa Barbara, in 2006. He was a Postdoctoral Associate at the University of … 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)
Makan Fardad Home CV : Research Publications Google Scholar Software : Teaching ELE 612/412 ELE 791 : College of Engineering & Computer Science 3-189 SciTech Syracuse University New York 13244 Tel: +1 (315) 443-4406 Fax: +1 (315) 443-4936 Email: [email protected] where x=makan, y=syr, z=edu ...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. for example Fardad_ELE603_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.
AU - Fardad, Makan. AU - Jovanovic, Mihailo. PY - 2013. Y1 - 2013. N2 - We design sparse and block sparse feedback gains that minimize the variance amplification (i.e., the {\cal H}2 norm) of distributed systems. Our approach consists of two steps. First, we identify sparsity patterns of feedback gains by incorporating sparsity-promoting ... ELE791 HW3 M.Fardad 1. [B&V, problem 3.6] When is the epigraph of a function a halfspace? When is the epigraph of a function a polyhedron? 2. [B&V, problems 3.18,20] Adapt the proof of convexity of the negative log-determinant function dis-cussed in class to show that f(X) = trace(X 1) is convex on domf = Sn ++. Use this to prove the
Recommended citation: Li, Jiayu, Tianyun Zhang, Hao Tian, Shengmin Jin, Makan Fardad, and Reza Zafarani. “SGCN: A Graph Sparsifier Based on Graph Convolutional Networks.” Advances in Knowledge Discovery and Data Mining 12084: 275. Share on Twitter Facebook LinkedIn Previous Next ELE791 HW3 M.Fardad 1. [B&V, problem 3.6] When is the epigraph of a function a halfspace? When is the epigraph of a function a polyhedron? 2. [B&V, problems 3.18,20] Adapt the proof of convexity of the negative log-determinant function dis-cussed in class to show that f(X) = trace(X 1) is convex on domf = Sn ++. Use this to prove theWe present a systematic weight pruning framework of deep neural networks (DNNs) using the alternating direction method of multipliers (ADMM). We first formulate the weight pruning problem of DNNs as a constrained nonconvex optimization problem, and then adopt the ADMM framework for systematic weight pruning. We show that ADMM is highly suitable ...Tianyun Zhang, Shaokai Ye, Yipeng Zhang, Yanzhi Wang & Makan Fardad Department of Electrical Engineering and Computer Science Syracuse University, Syracuse, NY 13244, USA ftzhan120,sye106,yzhan139,ywang393,[email protected] ABSTRACT We present a systematic weight pruning framework of deep neural networksAuthors. 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.
Teaching. ELE 400. ELE 603. ELE 603 - Functional Methods of Engineering Analysis - Fall 2023. Syllabus. Lecture Notes. All lecture notes as one file. Supplementary Texts. Text 1.
[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
Filter by Year. OR AND NOT 1. 2001Apr 27, 2018 · Investigating Shocks to the System, Fardad Receives CAREER Award. Friday, April 27, 2018, By Matt Wheeler. Awards College of Engineering and Computer Science faculty. Makan Fardad. On an average day in India not so long ago, the circuit breakers on a single powerline got tripped. That caused the breakers on another line to go down. Then another. Recommended citation: Li, Jiayu, Tianyun Zhang, Hao Tian, Shengmin Jin, Makan Fardad, and Reza Zafarani. “SGCN: A Graph Sparsifier Based on Graph Convolutional Networks.” Advances in Knowledge Discovery and Data Mining 12084: 275. Share on Twitter Facebook LinkedIn Previous Next Wayfinding and information design is on the frontlines in Ukraine Ukravtodor, the state agency in charge of Ukraine’s highways and road signs, is playing a tactical role in slowing...Authors: Shaokai Ye, Tianyun Zhang, Kaiqi Zhang, Jiayu Li, Kaidi Xu, Yunfei Yang, Fuxun Yu, Jian Tang, Makan Fardad, Sijia Liu, Xiang Chen, Xue Lin, Yanzhi Wang (Submitted on 17 Oct 2018 , last revised 4 Nov 2018 (this version, v2)) Abstract: Deep neural networks (DNNs) although achieving human-level performance in many domains, …
Makan Fardad. Syracuse University, Department of Electrical Engineering & Computer Science. h-index. 2100. Citations. 22. h-index. 2001 2022. Research activity per year. …Search within Makan Fardad's work. Search Search. Home; Makan FardadDownload a PDF of the paper titled Design of optimal sparse interconnection graphs for synchronization of oscillator networks, by Makan Fardad and 2 other authors Download PDF Abstract: We study the optimal design of a conductance network as a means for synchronizing a given set of oscillators.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. M. Fardad On Optimality of Sparse Long-Range Links in Circulant Consensus Networks IEEE Transactions on Automatic Control, vol. 62, pp. 4050-4057, …Makan Fardad. M. Fardad On Optimality of Sparse Long-Range Links in Circulant Consensus Networks IEEE Transactions on Automatic Control, vol. 62, pp. 4050-4057, …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 …
Makan Fardad. Makan Fardad. This person is not on ResearchGate, or hasn't claimed this research yet. Mihailo Jovanovic. University of Southern California; Download full-text PDF Read full-text.
Engineering & Computer Science, Syracuse University - Cited by 3,690 - Analysis and optimization of large-scale networksZhao, 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 and Bassam Bamieh. A Necessary and Sufficient Frequency Domain Criterion for the Passivity of SISO Sampled-Data Systems. IEEE Transactions on Automatic Control, 54(3):611-614, March 2008. Keyword(s): Sampled-Data Systems. M. Fardad and B. …Authors: Shaokai Ye, Tianyun Zhang, Kaiqi Zhang, Jiayu Li, Kaidi Xu, Yunfei Yang, Fuxun Yu, Jian Tang, Makan Fardad, Sijia Liu, Xiang Chen, Xue Lin, Yanzhi Wang (Submitted on 17 Oct 2018 , last revised 4 Nov 2018 (this version, v2)) Abstract: Deep neural networks (DNNs) although achieving human-level performance in many domains, …Makan Fardad Engineering & Computer Science, Syracuse University Verified email at syr.edu Sven Leyffer Senior Computational Mathematician, Argonne National Laboratory Verified email at anl.gov Neil K Dhingra Director -- Optimization and Machine Learning Verified email at umn.edu Teaching. ELE 612/412. ELE 791. ELE 791 - Convex Optimization - Spring 2024. Syllabus. Textbook. Lecture Notes. All lecture notes as one file. Homework & Solutions.
A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. T Zhang, X Ma, Z Zhan, S Zhou, C Ding, M Fardad, Y Wang. 2021 58th ACM/IEEE Design Automation Conference (DAC), 493-498. , 2021. 26 *. 2021. An image enhancing pattern-based sparsity for real-time inference on mobile devices.
Makan Fardad. Electrical Eng. & Computer Sci. 3-189 SciTech, Syracuse Univ. Syracuse, NY 13244. Tel: (805) 280{1232 Email: [email protected] http://ecs.syr.edu/faculty/fardad. Academic Appointments. Associate Professor Syracuse University, May 2018 { present Department of Electrical Engineering & Computer Science.
Tianyun Zhang, Shaokai Ye, Yipeng Zhang, Yanzhi Wang & Makan Fardad Department of Electrical Engineering and Computer Science Syracuse University, Syracuse, NY 13244, USA ftzhan120,sye106,yzhan139,ywang393,[email protected] ABSTRACT We present a systematic weight pruning framework of deep neural networksThe electric power grid is a complex cyber-physical system, whose reliable and secure operation is of paramount importance to national security and economic vitality. There is a growing and evolving t...This site is created, maintained, and managed by Conference Catalysts, LLC. Please feel free to contact us for any assistance.contact us for any assistance.Syracuse University. New York 13244. Tel: +1 (315) 443-4406. Fax: +1 (315) 443-4936. Email: [email protected] where x=makan, y=syr, z=edu. Research Interests. Convex optimization. Design and optimal control of complex networks. Synchronization and consensus in multi-agent systems.Apr 26, 2024 · 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, salvage Makan Fardad Home CV : Research Publications Google Scholar Software : Teaching ELE 612/412 ELE 791 : College of Engineering & Computer Science 3-189 SciTech Syracuse University New York 13244 Tel: +1 (315) 443-4406 Fax: +1 (315) 443-4936 Email: [email protected] where x=makan, y=syr, z=edu ...Tianyun Zhang, Shaokai Ye, Yipeng Zhang, Yanzhi Wang & Makan Fardad Department of Electrical Engineeringand ComputerScience Syracuse University, Syracuse, NY 13244,USA {tzhan120,sye106,yzhan139,ywang393,makan}@syr.edu ABSTRACT We present a systematic weight pruning framework of deep neural networksMakan Fardad Pron.: Maa-'kaan Far-'dad Associate Professor Electrical Engineering & Computer Science : EECS | ECS | SU: Makan Fardad Home CV : Research …Department of Electrical Engineering and Computer Science, Syracuse University, NY 13244, (e-mail: [email protected]) Abstract: We consider the problem of identifying optimal sparse graph representations of dense consensus networks. The performance of the sparse representation is characterized by the global performance measure which quanti es the ...Fu Lin, Makan Fardad, and Mihailo R. Jovanovic Abstract— We consider the design of optimal state feedback gains subject to structural constraints on the distributed controllers.
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}, …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, …Widespread theatrical closures have forced the Academy of Motion Picture Arts and Sciences to loosen the rules around which films qualify for Oscars. This might not seem like much ...Experience. Associate Professor. Syracuse University. View makan fardad’s profile on LinkedIn, the world’s largest professional community. makan has 1 job listed on their profile. See the...Instagram:https://instagram. aleli alcalapunlix bogojon loufman wifenatera turnaround time 2023 Jun 9, 2019 · Adversarial Attack Generation Empowered by Min-Max Optimization. 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 ... ottumwa 8 theatre photosroadhouse 48 China is a huge country with a wide variety of landforms, from the southwestern Himalayan Mountains, including Mount Everest on the Nepal-China border and the massive Gobi and Takl...Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney. In the context of distributed estimation, we consider the problem of sensor collaboration, which … walgreens blackhawk College of Engineering and Computer Science at Syracuse ...We consider the design of optimal localized feedback gains for one-dimensional formations in which vehicles only use information from their immediate neighbors.Abstract. In this paper, we consider the problem of sensor selection for parameter estimation with correlated measurement noise. We seek optimal sensor activations by formulating an optimization problem, in which the estimation error, given by the trace of the inverse of the Bayesian Fisher information matrix, is minimized subject to energy ...