Makan fardad.

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. Things To Know About Makan fardad.

Two ECS faculty members have earned National Science Foundation (NSF) CAREER Awards! Please join us in congratulating Assistant Professors Makan Fardad and Ian D. Hosein.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.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, Fu Lin, and Mihailo R. Jovanovi c´ Abstract We consider the design of optimal static feedback gains for interconnected systems subject to architectural con-straints on the distributed controller. These constraints are in the form of sparsity requirements for the feedback matrix, which means that each controller has access to ...

Assistant Professor Makan Fardad is exposing minor failures in infrastructure networks to stop them from snowballing into full-blown catastrophes.

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.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 ...

To address these ques-tions, we propose Sparsified Graph Convolutional Network (SGCN), a neural network graph sparsifier that sparsifies a graph by pruning some edges. We formulate sparsification as an optimization problem, which we solve by an Alternating Direction Method of Multipliers (ADMM)-based solution.Makan Fardad Pron.: Maa-'kaan Far-'dad Associate Professor Electrical Engineering & Computer Science : EECS | ECS | SU: Makan Fardad Home CV : Research … Liu, Sijia ; Masazade, Engin ; Fardad, Makan et al. / Sensor selection with correlated measurements for target tracking in wireless sensor networks. 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 4030-4034 (ICASSP, IEEE ... Makan 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 ...Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney. In the context of distributed estimation, we consider the problem of sensor collaboration, which …

Many people associate depression with sadness, but there are other signs, too. Learn about depression without sadness here. Most people associate depression with excessive sadness ...

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

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, …Tianyun Zhang, Kaiqi Zhang, Shaokai Y e, Jiayu Li, Jian T ang, Wujie W en, Xue Lin, Makan Fardad, and Y anzhi Wang. Adam-admm: A unified, systematic framework of structured weight pruning for dnns.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 networksTeaching. 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.

Oct 16, 2018 · Research Portal ... Powered by 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, … M. Fardad and B. Bamieh. An Extension of the Argument Principle and Nyquist Criterion to a Class of Systems with Unbounded Generators. IEEE Transactions on Automatic Control, 53(1):379-384, 2008. Keyword(s): Distributed and PDE Systems Theory. Makan Fardad and Bassam Bamieh. 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. These constraints are in the form of sparsity requirements for the feedback matrix, implying that each controller has access to information fromMakan Fardad. Syracuse University, Department of Electrical Engineering & Computer Science. h-index. 2100. Citations. 22. h-index. 2001 2022. Research activity per year. …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.

Griffin M. Kearneya,b1, Makan Fardadb2 aOpB Data Insights LLC, Syracuse, NY 13224 bSyracuse University, Syracuse, NY 13244 Abstract We develop a general framework for state estimation in systems modeled with noise-polluted con-tinuous time dynamics and discrete time noisy measurements. Our approach is based on maximum

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 Fu Lin, Makan Fardad, and Mihailo R. Jovanovi´c Abstract We design sparse and block sparse feedback gains that minimize the variance amplification (i.e., the H 2 norm) of distributed systems. Our approach consists of two steps. First, we identify sparsity Dr. Makan Fardad: Consensus-Based Community Detection in Dynamical Networks: Thurs, Apr 7 : Dr. Piya Pal: Smart Sampling For High Dimensional Inverse Problems: Thurs, Apr 14 : Dr. Raviraj S. Adve: Analysis, Algorithms and Design Tools for Wireless Networks: Tues, Apr 19 : Dr. Yingbin Liang: Kernel-based Detection of Anomalous Structures over ...Makan Fardad Pron.: Maa-'kaan Far-'dad Associate Professor Electrical Engineering & Computer Science : EECS | ECS | SU: Makan Fardad Home CV : Research Publications Google Scholar Software : Teaching ELE 400 ELE 603 : ELE 603 - Functional Methods of Engineering Analysis - Fall 2023 : Syllabus : Lecture ...College of Engineering and Computer Science at Syracuse University ...Makan Fardad Engineering & Computer Science, Syracuse University Verified email at syr.edu. Chilukuri Mohan Professor, Electrical Eng. & Computer Science, ... S Liu, SP Chepuri, M Fardad, E Maşazade, G Leus, PK Varshney. IEEE Transactions on Signal Processing 64 (13), 3509-3522, 2016. 203: 2016: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, Fu Lin, and Mihailo R. Jovanovi´c Abstract We study the optimal design of a conductance network as a means for synchronizing a given set of oscillators. Synchronization is achieved when all oscillator voltages reach consensus, and performance is quantified by the mean-square deviation from the consensus value.EE263 Prof. S. Boyd Crimes Against Matrices In this note we list some matrix crimes that we have, sadly, witnessed too often. Be very careful to avoid committing any of these crimes; in EE263 we have a zero-tolerance policy for

2-212 Center of Science & Technology Syracuse University Syracuse, NY 13244 315.443.1060

Oct 16, 2018 · Research Portal ... Powered by

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.[10] Tianyun Zhang, Kaiqi Zhang, Shaokai Ye, Jiayu Li, Jian Tang, Wujie Wen, Xue Lin, Makan Fardad, and Yanzhi Wang. Adam-admm: A unified, systematic framework of structured weight pruning for dnns. arXiv preprint arXiv:1807.11091, 2018. [11] Shaokai Ye and et al. Progressive weight pruning of deep neural networks using admm. arXiv preprintAdversarial 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 ...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.Tianyun Zhang, Shaokai Ye, Kaiqi Zhang, Jian Tang, Wujie Wen, Makan Fardad and Yanzhi Wang. ECCV 2018 (2018-09-08) ui.adsabs.harvard.edu PDF. Publications collected and formatted using Paperoni. 6666 St-Urbain, #200, Montréal, QC, H2S 3H1. Supervision Requests [email protected]. Medias [email protected] this work, we overcome pruning ratio and GPU acceleration limitations by proposing a unified, systematic framework of structured weight pruning for DNNs, named ADAM-ADMM (Adaptive Moment Estimation-Alternating Direction Method of Multipliers). It is a framework that can be used to induce different types of structured sparsity, such as filter ...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.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... 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. If you drive a relatively new car, there are usually a few sensors and cameras in place to help keep you safe. Here are the six major sensors on your car you should look for and ke...Oct 17, 2018 · 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 ( v1 ), last revised 4 Nov 2018 (this version, v2)) 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 networks

Recruiter.com Group News: This is the News-site for the company Recruiter.com Group on Markets Insider Indices Commodities Currencies StocksS. Liu, M. Fardad and P.K. Varshney are with the Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, 13244 USA e-mail: fsliu17, makan, [email protected]. S.P. Chepuri and G. Leus are with the Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, The ...2-212 Center of Science & Technology Syracuse University Syracuse, NY 13244 315.443.1060Instagram:https://instagram. eos 4th of july hours 2023us mint policewoe it's me crosswordrodrigues family snark AU - Fardad, Makan. AU - Lin, Fu. AU - Jovanović, Mihailo R. PY - 2010. Y1 - 2010. N2 - We use the dual decomposition method along with the dual subgradient algorithm to decouple the linear quadratic optimal control problem for a system of single-integrator vehicles. This produces the optimal control law in a localized manner, in the sense ... blue chip barberjim flowers omaha weather 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... are you supposed to refrigerate ozempic The M.S. in Operations Research and System Analytics is a 30-credit program that comprises 15 credits of core coursework, 12 credits of relevant electives, and 3 credits of a capstone project. The core ensures that all graduates of the program have the necessary skills in mathematics, operations research, engineering, and computing to …In the context of distributed estimation, we study the problem of sensor collaboration with individual power constraints, where sensor collaboration refers to the act of sharing measurements with neighboring sensors prior to transmission to a fusion center.