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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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arXiv 2020年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Electrical Engineering University of North Texas DentonTX76203 United States The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is considered. This problem is an important component of many machine learning techniques with data parallelism, such as deep learning and federated learning. We propose a distributed primal–dual stochastic gradient descent (SGD) algorithm, suitable for arbitrarily connected communication networks and any smooth (possibly nonconvex) cost functions. We show that the proposed algorithm achieves the linear speedup convergence rate O(1/√nT) for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak–Lojasiewicz (P–L) condition, where T is the total number of iterations. We also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global optimum. We demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Cost functions

Front Cover: Micrometer-Sized Liposome-Based Systems: A Hierarchical Breakdown (ChemSystemsChem 3/2025)

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ChemSystemsChem

ChemSystemsChem 2025年第3期7卷

作者： Prof. Dr. Shogo Hamada Dr. Hironori Sugiyama Prof. Dr. Yiting Zhang Prof. Dr. Shoji Iwabuchi Soichiro Hiroi Toshiki Maruyama Yuktesh Balaji Sota Kumagai Prof. Dr. Satoshi Murata Prof. Dr. Taro Toyota Department of Computer Science School of Computing & Department of Systems and Control Engineering School of Engineering Institute of Science Tokyo 4259 Nagatsuta-cho Midori-ku Yokohama-city Kanagawa 226-8501 Japan These authors contributed equally. Department of Applied Chemistry Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Department of Chemistry College of Science Rikkyo University 3-34-1 Nishi-Ikebukuro Toshima-ku Tokyo 171-8501 Japan Department of Biotechnology and Life Science Tokyo University of Agriculture and Technology 2-24-16 Naka-cho Koganei-shi Tokyo 185-8588 Japan Department of Basic Science Graduate School of Arts and Sciences The University of Tokyo 3-8-1 Komaba Meguro-ku Tokyo 153-8902 Japan Department of Robotics Graduate School of Engineering Tohoku University 6-6-01 Aramaki-Aza Aoba Aoba-ku Sendai Miyagi 980-8579 Japan Universal Biology Institute The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan

Spherical interpolated convolutional network with distance-feature density for 3D semantic segmentation of point clouds

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arXiv 2020年

作者： Wang, Guangming Yang, Yehui Zhang, Huixin Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Computer Science and Technology University of Cambridge United Kingdom

The semantic segmentation of point clouds is an important part of the environment perception for robots. However, it is difficult to directly adopt the traditional 3D convolution kernel to extract features from raw 3D point clouds because of the unstructured property of point clouds. In this paper, a spherical interpolated convolution operator is proposed to replace the traditional grid-shaped 3D convolution operator. This newly proposed feature extraction operator improves the accuracy of the network and reduces the parameters of the network. In addition, this paper analyzes the defect of point cloud interpolation methods based on the distance as the interpolation weight and proposes the self-learned distance-feature density by combining the distance and the feature correlation. The proposed method makes the feature extraction of spherical interpolated convolution network more rational and effective. The effectiveness of the proposed network is demonstrated on the 3D semantic segmentation task of point clouds. Experiments show that the proposed method achieves good performance on the ScanNet dataset and Paris-Lille-3D dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantic Segmentation

An Early Stage Researcher's Primer on Systems Medicine Terminology

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Network and Systems Medicine

Network and Systems Medicine 2021年第1期4卷 2-50页

作者： Zanin, Massimiliano Aitya, Nadim A.A. Basilio, José Baumbach, Jan Benis, Arriel Behera, Chandan K. Bucholc, Magda Castiglione, Filippo Chouvarda, Ioanna Comte, Blandine Dao, Tien-Tuan Ding, Xuemei Pujos-Guillot, Estelle Filipovic, Nenad Finn, David P. Glass, David H. Harel, Nissim Iesmantas, Tomas Ivanoska, Ilinka Joshi, Alok Boudjeltia, Karim Zouaoui Kaoui, Badr Kaur, Daman Maguire, Liam P. McClean, Paula L. McCombe, Niamh De Miranda, João Luís Moisescu, Mihnea Alexandru Pappalardo, Francesco Polster, Annikka Prasad, Girijesh Rozman, Damjana Sacala, Ioan Sanchez-Bornot, Jose M. Schmid, Johannes A. Sharp, Trevor Solé-Casals, Jordi Spiwok, Vojtěch Spyrou, George M. Stalidzans, Egils Stres, Blaa Sustersic, Tijana Symeonidis, Ioannis Tieri, Paolo Todd, Stephen Van Steen, Kristel Veneva, Milena Wang, Da-Hui Wang, Haiying Wang, Hui Watterson, Steven Wong-Lin, Kongfatt Yang, Su Zou, Xin Schmidt, Harald H.H.W. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Ulster United Kingdom Center for Physiology and Pharmacology Institute of Vascular Biology and Thrombosis Research Medical University of Vienna Vienna Austria TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany Holon Israel CNR National Research Council IAC Institute for Applied Computing Rome Italy Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont-Ferrand France Université de Technologie de Compiègne Compiègne France Labex MS2T Control of Technological Systems-of-Systems CNRS and Université de Technologie de Compiègne Compiègne France Faculty of Engineering University of Kragujevac Kragujevac Serbia Kragujevac Serbia Steinbeis Advanced Risk Technologies Institute Doo Kragujevac Kragujevac Serbia Pharmacology and Therapeutics School of Medicine Galway Neuroscience Centre National University of Ireland Galway Ireland School of Computing Ulster University Ulster United Kingdom Holon Israel Department of Mathematics and Natural Sciences Kaunas University of Technology Kaunas Lithuania Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia Medicine Faculty Université Libre de Bruxelles CHU de Charleroi Charleroi Belgium Northern Ireland Centre for Stratified Medicine Biomedical Sciences Research Institute Ulster University Ulster United Kingdom Escola Superior de Tecnologia e Gestão Instituto Politécnico de Portalegre Portalegre Portugal Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Faculty of Automatic Control and Computers University Politehnica of B

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic. © Massimiliano Zanin et al., 2021;Published by Mary Ann Liebert, Inc. 2021.

关键词： Semantics

SPAHN novel approach for PL-AG gateway discovery for internet connectivity

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Peer-to-Peer Networking and Applications 2020年第4期14卷 2275-2284页

作者： Kannan, K. Sivaranjani, P. Sathish Kumar, S. Nalini, M. Balaji, V. R. Sanjeevi, P. Department of ECE R.M.K. College of Engineering and Technology Chennai India Department of Electronics and communication Engineering Kongu Engineering College Erode India Dept of Electrical and Electronics Engineering M. Kumarasamy College of Engineering Thalavapalayam India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of ECE Sri Krishna College of Engineering and Technology Coimbatore India Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

Internet Gateway(IGW) main role is detecting availability nodes and providing internet to Mobile Ad Hoc Network(MANET) have whenever connected to internet. Discovery time of gateway is changed based on the throughput and packet delay. Many of the situations the mobile nodes are have fixed host connection to the internet using minimum hop path, it is not good for waiting packets because of that packets are have longer path interface queue. This research paper object is avoided above the problem mentioning using a novel approach of SPAHN (Solving Problem of Ad-Hoc Network). This paper mainly focus is classify the routing protocols of load-aware in MANET and from this classify discover the proactive load-aware gateway (PL-AG) from a device into interface queue size and min-hop-metric. This novel approach has been allowing and gives better handoff between two internet gateways for fixed host seamless connectivity. We justify the performance of the SPAHN approach using two metrics like average end-to-end delay and throughput based on this examination the SPAHN system yield good simulation results comparably existing systems.

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A registration-aided domain adaptation network for 3D Point cloud based place recognition

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arXiv 2020年

作者： Qiao, Zhijian Hu, Hanjiang Shi, Weiang Chen, Siyuan Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Mechanical Engineering Carnegie Mellon University United States Department of Computer Science and Technology University of Cambridge United Kingdom

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for registration in the real world. To this end, a novel registration-aided 3D domain adaptation network for point cloud based place recognition is proposed. A structure-aware registration network is introduced to help to learn features with geometric information and a 6-DoFs pose between two point clouds with partial overlap can be estimated. The model is trained through a synthetic virtual LiDAR dataset through GTA-V with diverse weather and daytime conditions and domain adaptation is implemented to the real-world domain by aligning the global features. Our results outperform state-of-the-art 3D place recognition baselines or achieve comparable on the real-world Oxford RobotCar dataset with the visualization of registration on the virtual dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

Design of Experiments for Battery Aging Estimation

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IFAC-PapersOnLine 2018年第28期51卷 386-391页

作者： Pózna, Anna I. Hangos, Katalin M. Magyar, Attila Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Egyetem str. 10. VeszprémH-8200 Hungary Process Control Research Group HAS Research Institute for Computer Science and Control Kende str. 13-17. BudapestH-1111 Hungary

Li-ion batteries are widely used in EV applications and are imposed to several aging effects during their lifetime. Since battery health cannot be measured directly, information about its health can be obtained by iteratively re-estimating the parameters of the model describing its dynamical behavior. The optimal design of experiments is investigated in this paper. The proposed method applies families of input signals (PRBS current and constant current-constant voltage (CC-CV) signals) to the batteries to estimate the key aging factors. Simulation experiments have been used to analyze the statistical properties of the estimators as a function of the design parameters of the input signal families. The results show that the CC-CV charging-discharging cycle has the possibility to gain the most information out of the battery model parameter estimation. © 2018

关键词： Parameter estimation Battery management systems Design of experiments Electric excitation Iterative methods Lithium ion batteries Planning Electric Experiment design Input Model formulation Storage operations

Building an Aerial-Ground robotics System for Precision Farming: An Adaptable Solution

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arXiv 2019年

作者： Pretto, Alberto Aravecchia, Stéphanie Burgard, Wolfram Chebrolu, Nived Dornhege, Christian Falck, Tillmann Fleckenstein, Freya Fontenla, Alessandra Imperoli, Marco Khanna, Raghav Liebisch, Frank Lottes, Philipp Milioto, Andres Nardi, Daniele Nardi, Sandro Pfeifer, Johannes Popović, Marija Potena, Ciro Pradalier, Cédric Rothacker-Feder, Elisa Sa, Inkyu Schaefer, Alexander Siegwart, Roland Stachniss, Cyrill Walter, Achim Winterhalter, Wera Wu, Xiaolong Nieto, Juan Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy International Research Lab 2958 Georgia Tech-CNRS Metz France Department of Computer Science University of Freiburg Germany Toyota Research Institute Los Altos United States Photogrammetry & Robotics Lab University of Bonn Germany Robert Bosch GmbH Corporate Research Renningen Germany Osimo Italy Autonomous Systems Lab. Department of Mechanical and Process Engineering ETH Zurich Zürich Switzerland Department of Environmental Systems Science Institute of Agricultural Sciences ETH Zurich Zürich Switzerland IT+Robotics Srl Padova Italy Smart Robotics Lab. Department of Computing Imperial College London London United Kingdom CSIRO Data61 Australia

The application of autonomous robots in agriculture is gaining increasing popularity thanks to the high impact it may have on food security, sustainability, resource use efficiency, reduction of chemical treatments, and the optimization of human effort and yield. With this vision, the Flourish research project aimed to develop an adaptable robotic solution for precision farming that combines the aerial survey capabilities of small autonomous unmanned aerial vehicles (UAVs) with targeted intervention performed by multi-purpose unmanned ground vehicles (UGVs). This paper presents an overview of the scientific and technological advances and outcomes obtained in the project. We introduce multi-spectral perception algorithms and aerial and ground-based systems developed for monitoring crop density, weed pressure, crop nitrogen nutrition status, and to accurately classify and locate weeds. We then introduce the navigation and mapping systems tailored to our robots in the agricultural environment, as well as the modules for collaborative mapping. We finally present the ground intervention hardware, software solutions, and interfaces we implemented and tested in different field conditions and with different crops. We describe a real use case in which a UAV collaborates with a UGV to monitor the field and to perform selective spraying without human intervention. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

Bio-Syncretic Light-gated Field-Effect Transistor: Fabrication and Characterization

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Bio-Syncretic Light-gated Field-Effect Transistor: Fabricati...

IEEE Conference on Nanotechnology

作者： Jia Yang Wenxue Wang Gongxin Li Guangyong Li Ning Xi Lianqing Liu State Key Laboratory of Robotics Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China State Key Laboratory of Robotics Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University Wuxi China Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh United States Emerging Technologies Institute University of Hong Kong Pokfulam Hong Kong

Biological visual system has many intrinsic functional superiorities, such as small size, high sensitivity and no heat-sink cooling, which are hard to be completely replicated by electromechanical systems. The bio-syncretic design of sensing device with living materials may provide some functional superiorities to those conventional sensing devices, and will have great potential benefits in both biomedical and engineering applications. In this study, we developed a novel bio-syncretic light-gated field-effect transistor (FET), in which optogenetically engineered cells were used as the gate substitute for conventional gate electrode, and the exposure of the cells to light irradiation results in the variation of the transistor's channel current. The bio-syncretic transistor was fabricated by virtue of graphene film and optogenetically engineered cells, and its basic photo-responsive performance was then tested and characterized. This reference-less bio-syncretic transistor has a wide range of potential applications in photodetection and biosensing with good biocompatibility and stability.

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