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arXiv 2025年

作者： Fang, Cheng Dixit, Rishabh Bajwa, Waheed U. Gürbüzbalaban, Mert Department of Electrical and Computer Engineering Rutgers University New BrunswickNJ United States Department of Mathematics University of California San DiegoCA United States Departments of Electrical and Computer Engineering and Statistics Rutgers University New BrunswickNJ United States Departments of Electrical and Computer Engineering Management Science and Information Systems and Statistics Rutgers University New BrunswickNJ United States

Empirical risk minimization (ERM) is a cornerstone of modern machine learning (ML), supported by advances in optimization theory that ensure efficient solutions with provable algorithmic convergence rates, which measure the speed at which optimization algorithms approach a solution, and statistical learning rates, which characterize how well the solution generalizes to unseen data. Privacy, memory, computational, and communications constraints increasingly necessitate data collection, processing, and storage across network-connected devices. In many applications, these networks operate in decentralized settings where a central server cannot be assumed, requiring decentralized ML algorithms that are both efficient and resilient. Decentralized learning, however, faces significant challenges, including an increased attack surface for adversarial interference during decentralized learning processes. This paper focuses on the man-in-the-middle (MITM) attack, wherein adversaries exploit communication vulnerabilities between devices to inject malicious updates during training, potentially causing models to deviate significantly from their intended ERM solutions. To address this challenge, we propose RESIST (Resilient dEcentralized learning using conSensus gradIent deScenT), an optimization algorithm designed to be robust against adversarially compromised communication links, where transmitted information may be arbitrarily altered before being received. Unlike existing adversarially robust decentralized learning methods, which often (i) guarantee convergence only to a neighborhood of the solution, (ii) lack guarantees of linear convergence for strongly convex problems, or (iii) fail to ensure statistical consistency as sample sizes grow, RESIST overcomes all three limitations. It achieves algorithmic and statistical convergence for strongly convex, Polyak–Lojasiewicz, and nonconvex ERM problems by employing a multistep consensus gradient descent framework and robust statis

关键词： Adversarial machine learning

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An Image Acquisition Scheme for Visual Odometry based on Image Bracketing and Online Attribute Control

An Image Acquisition Scheme for Visual Odometry based on Ima...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Shuyang Zhang Jinhao He Bohuan Xue Jin Wu Pengyu Yin Jianhao Jiao Ming Liu Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong SAR China Thrust of Robotics and Autonomous Systems the Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Center for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science University College London London UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Visual odometry (VO) system is challenged by complex illumination environments. Image quality and its consistency in the time domain directly determine feature detection and tracking performance, which further affect the robustness and accuracy of the entire system. In this paper, an image acquisition scheme with image bracketing patterns is proposed. Images with different exposure levels are continuously captured to sufficiently explore the scene under varying illumination. An attribute control method is designed to adjust image exposures within the brackets online. Gaussian process regression fits the relationship between image quality metric and exposure via image synthesis technique. The optimal exposures for the next bracket are obtained directly without attempts to ensure a quick response. Experiments show our acquisition system’s effectiveness and performance improvement for VO tasks in complex illumination scenes.

关键词： Image quality Measurement Image synthesis Lighting Gaussian processes Robustness Time-domain analysis

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Towards Satellite Non-IID Imagery: A Spectral Clustering-Assisted Federated Learning Approach

arXiv

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arXiv 2024年

作者： Zou, Luyao Park, Yu Min Thwal, Chu Myaet Tun, Yan Kyaw Han, Zhu Hong, Choong Seon Department of Computer Science and Engineering Kyung Hee University Yongin-si17104 Korea Republic of Department of Electronic Systems Aalborg University A. C. Meyers Vænge 15 København2450 Denmark Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States

Low Earth orbit (LEO) satellites are capable of gathering abundant Earth observation data (EOD) to enable different Internet of Things (IoT) applications. However, to accomplish an effective EOD processing mechanism, it is imperative to investigate: 1) the challenge of processing the observed data without transmitting those large-size data to the ground because the connection between the satellites and the ground stations is intermittent, and 2) the challenge of processing the nonindependent and identically distributed (non-IID) satellite data. In this paper, to cope with those challenges, we propose an orbit-based spectral clustering-assisted clustered federated self-knowledge distillation (OSC-FSKD) approach for each orbit of an LEO satellite constellation, which retains the advantage of FL that the observed data does not need to be sent to the ground. Specifically, we introduce normalized Laplacian-based spectral clustering (NLSC) into federated learning (FL) to create clustered FL in each round to address the challenge resulting from non-IID data. Particularly, NLSC is adopted to dynamically group clients into several clusters based on cosine similarities calculated by model updates. In addition, self-knowledge distillation is utilized to construct each local client, where the most recent updated local model is used to guide current local model training. Experiments demonstrate that the observation accuracy obtained by the proposed method is separately 1.01×, 2.15×, 1.10×, and 1.03× higher than that of pFedSD, FedProx, FedAU, and FedALA approaches using the SAT4 dataset. The proposed method also shows superiority when using other datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Satellite imagery

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Sentiment Analysis-Based Product Review System for Enhanced Recommendations

Sentiment Analysis-Based Product Review System for Enhanced ...

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Artificial Intelligence and Data engineering (AIDE), International Conference on

作者： Ashok Hake Jambukeshwar Pujari Lingaraju S V Naveen Kumar H S Department of Computer Science and Business Systems KIT’s College of Engineering(Autonomous) Kolhapur Maharashtra India Department of Mechanical Engineering T. K. I. E. T Warana University Warananagar Maharashtra India Department of Mechanical Engineering Government Polytechnic Holenarasipur Karnataka India

ISBN: (数字)9798331527518

ISBN: (纸本)9798331527525

The rapid growth of e-commerce has resulted in an overwhelming amount of user-generated content in the form of product reviews. Harnessing these reviews effectively is critical for enhancing recommendation systems. This paper presents a sentiment analysis-based approach that delves into specific product attributes, such as quality, design, price, durability, usability, comfort, value for money, and customer service, to extract actionable insights. By employing natural language processing (NLP) techniques, our system calculates both overall and attribute-specific sentiment scores, which are aggregated into a comprehensive recommendation score. The proposed methodology bridges the gap between unstructured text reviews and structured product recommendations, offering a detailed, attribute-focused perspective to improve user decision-making.

关键词： Sentiment analysis Reviews Statistical analysis Customer services Customer satisfaction User-generated content Tag clouds Electronic commerce Usability Recommender systems

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Wearable Sensor-based Multimodal Physiological Responses of Socially Anxious Individuals in Social Contexts on Zoom

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IEEE Transactions on Affective Computing 2025年

作者： Toner, Emma R. Rucker, Mark Wang, Zhiyuan Larrazabal, Maria A. Cai, Lihua Datta, Debajyoti Lone, Haroon Boukhechba, Mehdi Teachman, Bethany A. Barnes, Laura E. University of Virginia Department of Psychology CharlottesvilleVA United States University of Virginia Department of Systems and Information Engineering CharlottesvilleVA United States South China Normal University Aberdeen Institute of Data Science and Artificial Intelligence Guangzhou China Indian Institute of Science Education and Research Bhopal Department of Electrical Engineering and Computer Science Bhopal India Janssen Pharmaceutical Companies of Johnson & Johnson TitusvilleNJ United States

Correctly identifying an individual's social context from passively worn sensors holds promise for delivering justin-time adaptive interventions (JITAIs) to treat social anxiety. In this study, we present results using passively collected data from a within-subjects experiment that assessed physiological responses across different social contexts (i.e, alone vs. with others), social phases (i.e., pre- and post-interaction vs. during an interaction), social interaction sizes (i.e., dyadic vs. group interactions), and levels of social threat (i.e., implicit vs. explicit social evaluation). Participants in the study (N = 46) reported moderate to severe social anxiety symptoms as assessed by the Social Interaction Anxiety Scale (≥34 out of 80). Univariate paired difference tests, multivariate random forest models, and cluster analyses were used to explore physiological response patterns across different social and non-social contexts. Our results suggest that social context is more reliably distinguishable than social phase, group size, or level of social threat, and that there is considerable variability in physiological response patterns even among distinguishable contexts. Implications for real-world context detection and future deployment of JITAIs are discussed. © 2025 IEEE.

关键词： Wearable sensors

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An Approach for Repairing Incoherent Ontologies

An Approach for Repairing Incoherent Ontologies

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2021 International Semantic Web Conference Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters-Demos-Industry 2021

作者： Li, Ying Lambrix, Patrick Department of Computer and Information Science Linkoping University Sweden Swedish E-Science Research Centre Linkoping University Sweden Department of Building Engineering Energy Systems and Sustainability Science University of Gavle Sweden

The quality of ontologies and their alignments is crucial for developing high-quality ontology-based applications. In this paper we propose an approach for repairing incoherent ontologies and ontology networks that is... 详细信息

关键词： Ontology

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Learning Switching Port-Hamiltonian systems with Uncertainty Quantification

arXiv

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arXiv 2023年

作者： Beckers, Thomas Jiahao, Tom Z. Pappas, George J. Department of Computer Science Vanderbilt University NashvilleTN37212 United States Department of Computer and Information Science University of Pennsylvania PhiladelphiaPA19104 United States Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States

Switching physical systems are ubiquitous in modern control applications, for instance, locomotion behavior of robots and animals, power converters with switches and diodes. The dynamics and switching conditions are often hard to obtain or even inaccessible in case of a-priori unknown environments and nonlinear components. Black-box neural networks can learn to approximately represent switching dynamics, but typically require a large amount of data, neglect the underlying axioms of physics, and lack of uncertainty quantification. We propose a Gaussian process based learning approach enhanced by switching Port-Hamiltonian systems (GP-SPHS) to learn physical plausible system dynamics and identify the switching condition. The Bayesian nature of Gaussian processes uses collected data to form a distribution over all possible switching policies and dynamics that allows for uncertainty quantification. Furthermore, the proposed approach preserves the compositional nature of Port-Hamiltonian systems. A simulation with a hopping robot validates the effectiveness of the proposed approach. © 2023, CC BY-NC-ND.

关键词： Gaussian distribution

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Data Augmentation for Detection of Bacteria from Gram Stained Smears Images by YOLOv8

Data Augmentation for Detection of Bacteria from Gram Staine...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Ryunosuke Nakajo Minori Tsutsui Kouichi Hirata Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Department of Artificial Intelligence Kyushu Institute of Technology Iizuka Japan NS Solutions Kyushu Corporation

ISBN: (数字)9798350377903

ISBN: (纸本)9798350377910

In this paper, we investigate the methods of data augmentation appropriate to detect bacteria from Gram stained smears images by YOLOv8. For data augmentation, we adopt the flipping, the rotation, the cutout and the change of the values in HSB color space. Then, we evaluate these methods and the methods of the cutout and the change of the values in HSB color space after applying the flipping and the rotation.

关键词： YOLO Image color analysis Noise Data augmentation Bacteria Informatics

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Active RIS-Aided Massive MIMO With Imperfect CSI and Phase Noise

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IEEE Transactions on Wireless Communications 2025年

作者： Peng, Zhangjie Zhu, Jianchen Pan, Cunhua Zhang, Zaichen Da Costa, Daniel Benevides Elkashlan, Maged Karagiannidis, George K. Shanghai Normal University College of Information Mechanical and Electrical Engineering Shanghai200234 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Interdisciplinary Research Center for Communication Systems and Sensing Department of Electrical Engineering Dhahran31261 Saudi Arabia Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Greece Artificial Intelligence and Cyber Systems Research Center Lebanon

As a recently proposed reconfigurable intelligent surface (RIS) architecture, active RIS has drawn considerable interest. The important feature of the active RIS is its ability to strengthen the impinging signals to mitigate the multiplicative fading effect inherent in passive RIS-aided systems. Herein, we explore the performance of an active RIS-aided uplink multi-user massive multiple-input multiple-output (MIMO) system, considering the phase noise at the RIS. Furthermore, a two-timescale scheme is utilized, where the base station (BS) beamforming is designed based on the instantaneous aggregated channel state information (CSI), while the statistical CSI is used for designing the phase shifts of the active RIS. In addition, the linear minimum mean square error (LMMSE) estimator is adopted to estimate the aggregated channel, which combines both the cascaded and direct channels. According to the estimated channel, a closedform expression for the lower bound of achievable rate is derived. Based on the theoretical expressions, the power scaling laws for the considered system are also investigated. Specifically, when each user’s transmit power is proportionally reduced by the quantity of BS antennas M or RIS elements N, we find that the amplified thermal noise causes the lower bound of the achievable rate to approach zero as M or N tends to infinity. Moreover, an optimization approach based on a genetic algorithm (GA) is introduced to obtain the optimal phase shifts for maximizing the achievable rate. Numerical results reveal that the active RIS can greatly enhance the performance of the massive MIMO system compared to its passive counterpart. © 2002-2012 IEEE.

关键词： Genetic algorithms

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Convex Ternary Quartics Are SOS-Convex

arXiv

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arXiv 2024年

作者： Ahmadi, Amir Ali Blekherman, Grigoriy Parrilo, Pablo A. The Department of Operations Research and Financial Engineering Princeton University United States The School of Mathematics The Georgia Institute of Technology United States The Laboratory for Information and Decision Systems The Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States

We show that if a ternary quartic form is convex, then it must be sos-convex;i.e, if the Hessian H(x) of a ternary quartic form is positive semidefinite for all x, then the biquadratic form yT H(x)y in the variables x:= (x1, x2, x3)T and y:= (y1, y2, y3)T must be a sum of squares. This result is in a meaningful sense the "convex analogue" of Hilbert’s celebrated theorem on ternary quartics. We show that exploiting the structure of the Hessian matrix is crucial in any possible proof of this result by presenting an explicit example of a biquadratic form b(x, y) that is symmetric in x and y, nonnegative, but not a sum of squares. © 2024, CC BY.

关键词： Matrix algebra

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