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Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking

IEEE Transactions on Signal Processing 2025年

作者： Chen, Jun Liu, Lina Zhu, Tianyi Liu, Yong Dai, Guang Jiang, Yunliang Tsang, Ivor W. Zhejiang Normal University National Special Education Resource Center for Children with Autism Hangzhou311231 China Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China China Mobile Research Institute Beijing100032 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China State Grid Corporation of China SGIT AI Lab China Zhejiang Normal University Zhejiang Key Laboratory of Intelligent Education Technology and Application Jinhua321004 China Huzhou University School of Information Engineering Huzhou313000 China Centre for Frontier Artificial Intelligence Research A*STAR Singapore

This paper considers the problem of decentralized optimization on compact submanifolds, where a finite sum of smooth (possibly non-convex) local functions is minimized by n agents forming an undirected and connected graph. However, the efficiency of distributed optimization is often hindered by communication bottlenecks. To mitigate this, we propose the Quantized Riemannian Gradient Tracking (Q-RGT) algorithm, where agents update their local variables using quantized gradients. The introduction of quantization noise allows our algorithm to bypass the constraints of the accurate Riemannian projection operator (such as retraction), further improving iterative efficiency. To the best of our knowledge, this is the first algorithm to achieve an O(1/K) convergence rate in the presence of quantization, matching the convergence rate of methods without quantization. Additionally, we explicitly derive lower bounds on decentralized consensus associated with a function of quantization levels. Numerical experiments demonstrate that Q-RGT performs comparably to non-quantized methods while reducing communication bottlenecks and computational overhead. © 1991-2012 IEEE.

关键词： Iterative methods

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Attack surface identification and reduction model applied in scrum 5

Attack surface identification and reduction model applied in...

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5th International Conference on Cyber Security and Protection of Digital Services, Cyber Security 2019

作者： Yee, George O.M. Computer Research Lab Aptusinnova Inc. Dept. of Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9781728102290

Today's software is full of security vulnerabilities that invite attack. Attackers are especially drawn to software systems containing sensitive data. For such systems, this paper presents a modeling approach especially suited for Serum or other forms of agile development to identify and reduce the attack surface. The latter arises due to the locations containing sensitive data within the software system that are reachable by attackers. The approach reduces the attack surface by changing the design so that the number of such locations is reduced. The approach performs these changes on a visual model of the software system. The changes are then considered for application to the actual system to improve its security. © 2019 IEEE.

关键词： computer software

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Robust Load Frequency Control of Two-Area Interconnected Power System Using Fuzzy-I Controller

Robust Load Frequency Control of Two-Area Interconnected Pow...

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2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Wazir, Awadh Ba Alhussainy, Abdullah Ali Alghamdi, Sultan Rawa, Muhyaddin Sindi, Hatem F. King Abdulaziz University K. A. CARE Energy Research and Innovation Center Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Jeddah Saudi Arabia King Abdulaziz University Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Jeddah Saudi Arabia King Abdulaziz University Electrical and Computer Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798350331790

The paper proposes a Fuzzy-I controller for optimal load frequency control (LFC) in a two-area interconnected power system. The proposed controller is composed of a fuzzy logic controller (FLC) and an integral (I) controller. To achieve a better dynamic response for the LFC, the integral controller and frequency bias parameters of the secondary loop are tuned using the Particle Swarm Optimization (PSO) technique. To boost the efficiency of the optimization, a proposed objective function using the integral of squared error (ISE) and settling time is used. A comparative study and analysis are conducted between the base system controller, optimized I controller, and the proposed controller under three different scenarios of load disturbances. The robustness of the proposed controller is shown by performing a sensitivity analysis for various system parameters and operating conditions. Moreover, the performance of the proposed controller was compared with the previous LFC approaches published in the literature. The simulation outcomes demonstrate that the proposed method has an outstanding performance. The work results are presented as time-domain simulations using MATlab/SIMULINK tool. © 2023 IEEE.

关键词： Controllers

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A digital processor for full calibration of pipelined ADCS

A digital processor for full calibration of pipelined ADCS

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2010 IEEE International Conference on Electronics, Circuits, and systems, ICECS 2010

作者： Fardad, Mohammad Frounchi, Javad Karimian, Ghader Microelectronic and Microsensor Research Lab. Faculty of Electrical and Computer Engineering University of Tabriz Iran Digital Systems Research Lab. Faculty of Electrical and Computer Engineering University OfTabriz Iran

ISBN: (纸本)9781424481576

A digital full calibration processor is proposed to calibrate most known errors in Pipe lined ADCs. This approach does not change internal parts of an ADC and compensates errors by digital post-processing of the output bits. The main idea behind the presented technique is to design a processor to find a correction function that gives the relation between the uncalibrated outputs and the calibrated ones. To verify the algorithm, a 12-bit pipelined ADC based on 1.5-bit per stage architecture is simulated with non ideal factors in the SIMULINK with a 5.34MHz sinusoidal input and a 100MHz sampling frequency. The SNDR is improved from 45dB to 69dB and the SFDR is increases from 45.5dB to 90dB. The described algorithm has been implemented on a virtex-4 LX25 FPGA from Xilinx. ©2010 IEEE.

关键词： Calibration

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Exploring the Effects of Social VR Coupling Modes on Engagement and Task Performance for Older Adults 25

Exploring the Effects of Social VR Coupling Modes on Engagem...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing systems

作者： Thuan T Vo Satabdi Das Shamim Noroozi Lakshay Dang Jaisie Sin Jennifer N Boger Jennifer Jakobi Khalad Hasan University of British Columbia Kelowna British Columbia Canada Computer Science The University of British Columbia Kelowna British Columbia Canada School of Engineering University of British Columbia-Okanagan Kelowna British Columbia Canada Okanagan Visualization and Interaction Lab The University of British Columbia Okanagan Kelowna British Columbia Canada Carleton University Ottawa Ontario Canada Systems Design Engineering University of Waterloo Waterloo Ontario Canada and The University of British Columbia British Columbia Canada Aging in Place Research Cluster The University of British Columbia Okanagan British Columbia Canada The University of British Columbia Okanagan Kelowna British Columbia Canada

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Optimizing Deep Learning for computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression

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computer Modeling in engineering & Sciences 2024年第3期138卷 2519-2547页

作者： Hassen Louati Ali Louati Elham Kariri Slim Bechikh College of Information Technology Kingdom UniversityRiffa40434Bahrain SMART Lab University of TunisISGTunisTunisia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Recent developments in computer Vision have presented novel opportunities to tackle complex healthcare issues,particularly in the field of lung disease *** promising avenue involves the use of chest X-Rays,which are commonly utilized in *** fully exploit their potential,researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic ***,constructing and compressing these systems presents a significant challenge,as it relies heavily on the expertise of data *** tackle this issue,we propose an automated approach that utilizes an evolutionary algorithm(EA)to optimize the design and compression of a convolutional neural network(CNN)for X-Ray image *** approach accurately classifies radiography images and detects potential chest abnormalities and infections,including ***,our approach incorporates transfer learning,where a pre-trainedCNNmodel on a vast dataset of chest X-Ray images is fine-tuned for the specific task of detecting *** method can help reduce the amount of labeled data required for the task and enhance the overall performance of the *** have validated our method via a series of experiments against state-of-the-art architectures.

关键词： computer-aided diagnosis deep learning evolutionary algorithms deep compression transfer learning

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Design of thrust ripple minimization in wound secondary linear synchronous motors by response surface methodology (RSM)

Design of thrust ripple minimization in wound secondary line...

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2011 2nd Power Electronics, Drive systems and Technologies Conference, PEDSTC 2011

作者： Hosseini, Monir Sadat Khameneh, Mehdi Mardaneh Vaez-Zadeh, Sadegh Advanced Motion Systems Research Lab School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781612844213

In this paper, after modeling and analyzing a single-sided wound secondary linear synchronous motor, single- and multi-objective design optimizations of the motor are carried out to develop larger average thrust and lower thrust ripple than the prototype by using design of experiments (DOE) and response surface methodology (RSM) considering multiple responses. By defining the motor weight as another objective function, it is tried to prevent an increase in motor size and reduce its material consumption. The optimization results confirm that desirable improvements in thrust mean, thrust ripple and motor weight are achieved. Finally, a finite element analysis is employed to evaluate the effectiveness of the employed machine models used in thrust and force ripple calculations and subsequently to confirm the proposed optimization method. © 2011 IEEE.

关键词： Optimization

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Adding privacy protection to distributed software systems 14

Adding privacy protection to distributed software systems

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14th International Joint Conference on e-Business and Telecommunications, ICETE 2017

作者： Yee, George O.M. Computer Research Lab Aptusinnova Inc. Ottawa Canada Department of Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9789897582592

Distributed software systems are increasingly found in many aspects of our lives, as can be seen in social media, international online banking, and international commerce (e.g. Internet shopping). This widespread involvement of software in our lives has led to the need to protect privacy, as the use of the software often requires us to input our personal or private information. A first step to protecting privacy is to identify the risks to privacy found in the software system. Once the risks are known, measures can be put in place to mitigate the risks. This is best done at the early stages of software development due to the heavy costs of making changes after the software is deployed. This paper proposes a two-pronged approach, consisting of privacy risk identification followed by risk mitigation, for adding privacy protection to distributed software. The paper illustrates the approach with examples. Copyright © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Data privacy

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Trusted framework for health information exchange

Trusted framework for health information exchange

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2011 9th International Conference on Frontiers of Information Technology, FIT 2011

作者： Afzal, Muhammad Hussain, Maqbool Ahmad, Mahmood Anwar, Zahid Semantic Systems Research Lab. School of Electrical Engineering and Computer Science Pakistan Department of Computing School of Electrical Engineering and Computer Science Pakistan

ISBN: (纸本)9780769546254

Healthcare Interchange Exchange (HIE) is set of healthcare entities that link regions and nations around the world to share healthcare information about patients. HIE provides a unified interface to various stakeholders to access patient data. For example, individuals want to access personal data, practitioners want to import their patient data from Personal Health Records (PHR) and researchers want to access anonymized patient data for research purposes with ensured individual privacy. Keeping in view requirements of various stakeholders it is challenging to design an HIE system that ensures the security and privacy of patient information, such that the health records remain interoperable and scalable. This paper proposes, an HIE framework that will provide secure access to patient data and adhere to the interoperability rules. Implementation of l-diversity algorithm ensures individual privacy especially when the data is made available publicly for statistical analysis. © 2011 IEEE.

关键词： Interoperability

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NetMind+: Adaptive Baseband Function Placement With GCN Encoding and Incremental Maze-Solving DRL for Dynamic and Heterogeneous RANs

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IEEE Transactions on Network and Service Management 2025年

作者： Li, Haiyuan Li, Peizheng Assis, Karcius Day Parra, Juan Marcelo Aijaz, Adnan Yan, Shuangyi Simeonidou, Dimitra University of Bristol High Performance Networks Group Smart Internet Lab Department of Electrical and Electronic Engineering BS8 1QU United Kingdom Toshiba Europe Ltd Bristol Research and Innovation Laboratory BS1 4ND United Kingdom Electrical and Computer Engineering Department Brazil

The disaggregated architecture of advanced Radio Access Networks (RANs) with diverse X-haul latencies, in conjunction with resource-limited multi-access edge computing networks, presents significant challenges in designing a general model in placing baseband and user plane functions to accommodate versatile 5G services. This paper proposes a novel approach, NetMind+, which leverages Deep Reinforcement Learning (DRL) to determine the function placement strategies in diverse and evolving RAN topologies, aiming at minimizing power consumption. NetMind+ resolves the problem with a maze-solving strategy, enabling a Markov Decision Process with standardized action space scales across different networks. Additionally, a Graph Convolutional Network (GCN) based encoding and an incremental learning mechanism are introduced, allowing features from different and dynamic networks to be aggregated into a single DRL agent. This facilitates the generalization capability of DRL and minimizes the negative retraining impact. In an example with three sub-networks, NetMind+ demonstrates a substantial 32.76% improvement in power savings and a 41.67% increase in service stability compared to benchmarks from the existing literature. Compared to traditional methods necessitating a dedicated DRL agent for each network, NetMind+ attains comparable performance with 70% of the training cost savings. Furthermore, it demonstrates robust adaptability during network variations, accelerating training speed by 50%. © 2004-2012 IEEE.

关键词： Deep reinforcement learning

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