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An accuracy-lossless perturbation method for defending privacy attacks in federated learning

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arXiv 2020年

作者： Yang, Xue Feng, Yan Fang, Weijun Shao, Jun Tang, Xiaohu Xia, Shutao Lu, Rongxing Tsinghua Shenzhen International Graduate School Tsinghua University Pcl Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China School of Computer and Information Engineering Zhejiang Gongshang University Zhejiang310018 China Information Security and National Computing Grid Laboratory Southwest Jiaotong University Chengdu610031 China Canadian Institute of Cybersecurity Faculty of Computer Science University of New Brunswick FrederictonE3B 5A3 Canada

Although federated learning improves privacy of training data by exchanging local gradients or parameters rather than raw data, the adversary still can leverage local gradients and parameters to obtain local training data by launching reconstruction and membership inference attacks. To defend such privacy attacks, many noises perturbation methods (like differential privacy or CountSketch matrix) have been widely designed. However, the strong defence ability and high learning accuracy of these schemes cannot be ensured at the same time, which will impede the wide application of FL in practice (especially for medical or financial institutions that require both high accuracy and strong privacy guarantee). To overcome this issue, in this paper, we propose an efficient model perturbation method for federated learning to defend reconstruction and membership inference attacks launched by curious clients. On the one hand, similar to the differential privacy, our method also selects random numbers as perturbed noises added to the global model parameters, and thus it is very efficient and easy to be integrated in practice. Meanwhile, the random selected noises are positive real numbers and the corresponding value can be arbitrarily large, and thus the strong defence ability can be ensured. On the other hand, unlike differential privacy or other perturbation methods that cannot eliminate the added noises, our method allows the server to recover the true gradients by eliminating the added noises. Therefore, our method does not hinder learning accuracy at all. Extensive experiments demonstrate that for both regression and classification tasks, our method achieves the same accuracy as non-private approaches and outperforms the state-ofthe- art related schemes. Besides, the defence ability of our method is significantly better than the state-of-the-art related defence schemes. Specifically, for the membership inference attack, our method achieves attack success rate (ASR) of aroun

关键词： Perturbation techniques

Electrically driven programmable phase-change meta-switch reaching 80% efficiency

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arXiv 2021年

作者： Abdollahramezani, Sajjad Hemmatyar, Omid Taghinejad, Mohammad Taghinejad, Hossein Krasnok, Alex Eftekhar, Ali A. Teichrib, Christian Deshmukh, Sanchit El-Sayed, Mostafa Pop, Eric Wuttig, Matthias Alù, Andrea Cai, Wenshan Adibi, Ali School of Electrical and Computer Engineering Georgia Institute of Technology 778 Atlantic Drive NW AtlantaGA30332-0250 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical Engineering Precourt Institute for Energy Stanford University StanfordCA94305 United States Laser Dynamics Laboratory School of Chemistry and Biochemistry Georgia Institute of Technology AtlantaGA30332-0400 United States George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332-0405 United States Physikalisches Institut IA RWTH Aachen Sommerfeldstrasse 14 Aachen52074 Germany Physics Program Graduate Center City University of New York New YorkNY10016 United States School of Materials Science and Engineering Georgia Institute of Technology 801 Ferst Drive NW AtlantaGA30332-0295 United States

Despite recent advances in active metaoptics, efficient wide dynamic range combined with highspeed reconfigurable solutions is still elusive. Phase-change materials (PCMs) offer a compelling platform for metasurface optical elements, owing to the large index contrast and fast yet stable phase transition properties. Here, we experimentally demonstrate an in situ electrically driven reprogrammable metasurface by harnessing the unique properties of a phase-change chalcogenide alloy, Ge2Sb2Te5 (GST), in order to realize non-volatile, reversible, multilevel, fast, and pronounced optical modulation in the near-infrared spectral range. Co-optimized through a multiphysics analysis, we integrate an efficient heterostructure resistive microheater that indirectly heats and transforms the embedded GST film without compromising the optical performance of the metasurface even after several reversible phase transitions. A hybrid plasmonic-PCM meta-switch with a record eleven-fold change in the reectance (an absolute reectance contrast reaching 80%), unprecedented quasi-continuous spectral tuning over 250 nm, and operation speed that can potentially reach a few kHz is presented. Our work represents a significant step towards the development of fully integrable dynamic metasurfaces and their potential for beamforming applications. © 2021, CC BY.

关键词： Phase change materials

Performance and Optimization of Reconfigurable Intelligent Surface Aided THz Communications

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arXiv 2020年

作者： Du, Hongyang Zhang, Jiayi Guan, Ke Niyato, Dusit Jiao, Huiying Wang, Zhiqin Kürner, Thomas The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The School of Computer Science and Engineering Nanyang Technological University Singapore China Academy of Information and Communications Technology Beijing100191 China Technische Universität Braunschweig Brunswick38106 Germany

TeraHertz (THz) communications can satisfy the high data rate demand with massive bandwidth. However, severe path attenuation and hardware imperfection greatly alleviate its performance. Therefore, we utilize the reconfigurable intelligent surface (RIS) technology and investigate the RIS-aided THz communications. We first prove that the small-scale amplitude fading of THz signals can be accurately modeled by the fluctuating two-ray distribution based on two THz signal measurement experiments conducted in a variety of different scenarios. To optimize the phase-shifts at the RIS elements, we propose a novel swarm intelligence-based method that does not require full channel estimation. We then derive exact statistical characterizations of end-to-end signal-to-noise plus distortion ratio (SNDR) and signal-to-noise ratio (SNR). Moreover, we present asymptotic analysis to obtain more insights when the SNDR or the number of RIS's elements is high. Finally, we derive analytical expressions for the outage probability and ergodic capacity. The tight upper bounds of ergodic capacity for both ideal and non-ideal radio frequency chains are obtained. It is interesting to find that increasing the number of RIS's elements can significantly improve the THz communications system performance. For example, the ergodic capacity can increase up to 25% when the number of elements increases from 40 to 80, which incurs only insignificant costs to the system. © 2020, CC BY.

关键词： Signal to noise ratio

Non-negative sparse and collaborative representation for pattern classification

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arXiv 2019年

作者： Xu, Jun Xu, Zhou An, Wangpeng Wang, Haoqian Zhang, David Media Computing Lab College of Computer Science Nankai University Tianjin China School of Computer Science Wuhan University Wuhan China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Shenzhen Institute of Future Media Technology Shenzhen China Shenzhen China

Sparse representation (SR) and collaborative representation (CR) have been successfully applied in many pattern classification tasks such as face recognition. In this paper, we propose a novel Non-negative Sparse and Collaborative Representation (NSCR) for pattern classification. The NSCR representation of each test sample is obtained by seeking a non-negative sparse and collaborative representation vector that represents the test sample as a linear combination of training samples. We observe that the non-negativity can make the SR and CR more discriminative and effective for pattern classification. Based on the proposed NSCR, we propose a NSCR based classifier for pattern classification. Extensive experiments on benchmark datasets demonstrate that the proposed NSCR based classifier outperforms the previous SR or CR based approach, as well as state-of-the-art deep approaches, on diverse challenging pattern classification tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Face recognition

Roadmap on Nonlocality in Photonic Materials and Metamaterials

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arXiv 2025年

作者： Monticone, Francesco Mortensen, N. Asger Fernández-Domínguez, Antonio I. Luo, Yu Tserkezis, Christos Khurgin, Jacob B. Shahbazyan, Tigran V. Chaves, André J. Peres, Nuno M.R. Wegner, Gino Busch, Kurt Hu, Huatian della Sala, Fabio Zhang, Pu Ciracì, Cristian Aizpurua, Javier Babaze, Antton Borisov, Andrei G. Chen, Xue-Wen Christensen, Thomas Yan, Wei Yang, Yi Hohenester, Ulrich Huber, Lorenz Wubs, Martijn de Liberato, Simone Gonçalves, P.A.D. de Abajo, F. Javier García Hess, Ortwin Tarasenko, Illya Cox, Joel D. Jelver, Line Dias, Eduardo J.C. Sánchez, Miguel Sánchez Margetis, Dionisios Gómez-Santos, Guillermo Stauber, Tobias Tretyakov, Sergei Simovski, Constantin Pakniyat, Samaneh Gómez-Díaz, J. Sebastián Bondarev, Igor V. Biehs, Svend-Age Boltasseva, Alexandra Shalaev, Vladimir M. Krasavin, Alexey V. Zayats, Anatoly V. Alù, Andrea Song, Jung-Hwan Brongersma, Mark L. Levy, Uriel Long, Olivia Y. Guo, Cheng Fan, Shanhui Bozhevolnyi, Sergey I. Overvig, Adam Prudêncio, Filipa R. Silveirinha, Mário G. Gangaraj, S. Ali Hassani Argyropoulos, Christos Huidobro, Paloma A. Galiffi, Emanuele Yang, Fan Pendry, John B. Miller, David A.B. School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States POLIMA Center for Polariton-driven Light–Matter Interactions University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark D-IAS—Danish Institute for Advanced Study University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark Departamento de Física Teórica de la Materia Condensada Universidad Autónoma de Madrid MadridE-28049 Spain Universidad Autónoma de Madrid MadridE-28049 Spain School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Physics Jackson State University JacksonMS39217 United States Department of Physics Aeronautics Institute of Technology SP So Jos dos Campos12228-900 Brazil Departamento de Física Universidade do Minho BragaP-4710-057 Portugal Av Mestre José Veiga Braga4715-330 Portugal Max-Born-Institut Berlin12489 Germany Humboldt-Universität zu Berlin Institut für Physik AG Theoretische Optik and Photonik Berlin12489 Germany Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Via Barsanti 14 Arnesano73010 Italy Via Monteroni Campus Unisalento Lecce73100 Italy School of physics Huazhong University of Science and Technology Luoyu Road 1037 Wuhan430074 China Donostia International Physics Center DIPC Donostia-San Sebastián20018 Spain Ikerbasque Basque Foundation for Science Bilbao48009 Spain Department of Electricity and Electronics University of the Basque Country Leioa48940 Spain Department of Applied Physics University of the Basque Country Donostia20018 Spain Université Paris-Saclay CNRS Institut des Scienc

Photonic technologies continue to drive the quest for new optical materials with unprecedented responses. A major frontier in this field is the exploration of nonlocal (spatially dispersive) materials, going beyond the local, wavevector-independent assumption traditionally made in optical material modeling. On one end, the growing interest in plasmonic, polaritonic and quantum materials has revealed naturally occurring nonlocalities, emphasizing the need for more accurate models to predict and design their optical responses. This has major implications also for topological, nonreciprocal, and time-varying systems based on these material platforms. Beyond natural materials, artificially structured materials—metamaterials and metasurfaces–can provide even stronger and engineered nonlocal effects, emerging from long-range interactions or multipolar effects. This is a rapidly expanding area in the field of photonic metamaterials, with open frontiers yet to be explored. In the case of metasurfaces, in particular, nonlocality engineering has become a powerful tool for designing strongly wavevector-dependent responses, enabling enhanced wavefront control, spatial compression, multifunctional devices, and wave-based computing. Furthermore, nonlocality and related concepts play a critical role in defining the ultimate limits of what is possible in optics, photonics, and wave physics. This Roadmap aims to survey the most exciting developments in nonlocal photonic materials, highlight new opportunities and open challenges, and chart new pathways that will drive this emerging field forward–toward new scientific discoveries and technological advancements. Copyright © 2025, The Authors. All rights reserved.

关键词： Nanocrystals

Corrigendum to "Novel model of multiple sclerosis induced by EBV-like virus generate a unique B cell population" [Journal of Neuroimmunology volume 394 (2024) 578408]

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Journal of neuroimmunology 2025年 404卷 578625页

作者： J L Deffenbaugh K-J Jung S P Murphy Y Liu C N Rau C Petersen-Cherubini P L Collins D Chung A E Lovett-Racke Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA. Department of Computer Science and Engineering The Ohio State University USA. Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA Neuroscience Graduate Program The Ohio State University USA. Department of Biomedical Informatics The Ohio State University Wexner Medical Center USA Pelotonia Institute for Immuno-Oncology The Ohio State University Wexner Medical Center USA. Department of Neuroscience The Ohio State University Wexner Medical Center USA. Electronic address: amylovettracke@***.

Tongue image segmentation via color decomposition and thresholding

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Tongue image segmentation via color decomposition and thresh...

作者： Li, Zuoyong Yu, Zhaochai Liu, Weixia Xu, Yong Zhang, Daoqiang Cheng, Yong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China The Fujian College's Research Base of Humanities and Social Science for Internet Innovation Research Center Minjiang University Fuzhou350121 China Straits Institute Minjiang University Fuzhou350121 China Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen518055 China Department of Computer Science and Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Communication Engineering Nanjing Institute of Technology Nanjing211167 China

Tongue image segmentation is a crucial step in developing an automatic tongue diagnosis system. After exploring characteristics of image thresholding in different color spaces, we propose a simple and effective tongue image segmentation method. Specifically, the proposed method first extracts an initial tongue body region by performing image thresholding on the transformed hue component in HSI (Hue, Saturation, and Intensity) color space. Then, one of two image thresholding results on the red component of an original tongue image is adaptively selected to find the gap region between the tongue body root and the upper lip. Finally, the initial tongue body region is refined by removing fake object regions such as the upper lip to obtain final tongue image segmentation result. Experimental results on a tongue image dataset containing 200 subjects demonstrate the effectiveness of the proposed method. © 2018 John Wiley & Sons, Ltd.

关键词： Image segmentation

Two-Step Electronic Response to Magnetic Ordering in a van der Waals Ferromagnet

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arXiv 2023年

作者： Wu, Han Zhu, Jian-Xin Chen, Lebing Butcher, Matthew W. Yue, Ziqin Yuan, Dongsheng He, Yu Oh, Ji Seop Huang, Jianwei Wu, Shan Gong, Cheng Guo, Yucheng Mo, Sung-Kwan Denlinger, Jonathan D. Lu, Donghui Hashimoto, Makoto Stone, Matthew B. Kolesnikov, Alexander I. Chi, Songxue Kono, Junichiro Nevidomskyy, Andriy H. Birgeneau, Robert J. Dai, Pengcheng Yi, Ming Department of Physics and Astronomy Rice Center for Quantum Materials Rice University HoustonTX77005 United States Theoretical Division Los Alamos National Laboratory Los AlamosNM87545 United States Center for Integrated Nanotechnologies Los Alamos National Laboratory Los AlamosNM87545 United States Department of Physics University of California at Berkeley BerkeleyCA94720 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States 1-1 Namiki Ibaraki Tsukuba305-0044 Japan Department of Applied Physics Yale University New HavenCT06511 United States Department of Electrical and Computer Engineering Quantum Technology Center University of Maryland College ParkMD20742 United States Advanced Light Source Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Stanford Synchrotron Radiation Lightsource SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Neutron Scattering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Material Science and NanoEngineering Rice University HoustonTX77005 United States Department of Materials Science and Engineering University of California Berkeley United States

The two-dimensional (2D) material Cr2Ge2Te6 is a member of the class of insulating van der Waals magnets. Here, using high resolution angle-resolved photoemission spectroscopy in a detailed temperature dependence study, we identify a clear response of the electronic structure to a dimensional crossover in the form of two distinct temperature scales marking onsets of modifications in the electronic structure. Specifically, we observe Te p-orbital-dominated bands to undergo changes at the Curie transition temperature TC while the Cr d-orbital-dominated bands begin evolving at a higher temperature scale. Combined with neutron scattering, density functional theory calculations, and Monte Carlo simulations, we find that the electronic system can be consistently understood to respond sequentially to the distinct temperatures at which in-plane and out-of-plane spin correlations exceed a characteristic length scale. Our findings reveal the sensitivity of the orbital-selective electronic structure for probing the dynamical evolution of local moment correlations in vdW insulating magnets. © 2023, CC BY.

关键词： Electronic structure

An Ensemble Approach for Emotion Cause Detection with Event Extraction and Multi-Kernel SVMs

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Tsinghua science and Technology 2017年第6期22卷 646-659页

作者： Ruifeng Xu Jiannan Hu Qin Lu Dongyin Wu Lin Gui School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School Department of Computing the Hong Kong Polytechnic University

In this paper, we present a new challenging task for emotion analysis, namely emotion cause *** this task, we focus on the detection of emotion cause a.k.a the reason or the stimulant of an emotion, rather than the regular emotion classification or emotion component extraction. Since there is no open dataset for this task available, we first designed and annotated an emotion cause dataset which follows the scheme of W3 C Emotion Markup Language. We then present an emotion cause detection method by using event extraction framework,where a tree structure-based representation method is used to represent the events. Since the distribution of events is imbalanced in the training data, we propose an under-sampling-based bagging algorithm to solve this problem. Even with a limited training set, the proposed approach may still extract sufficient features for analysis by a bagging of multi-kernel based SVMs method. Evaluations show that our approach achieves an F-measure 7.04%higher than the state-of-the-art methods.

关键词： emotion cause detection event extraction multi-kernel SVMs bagging