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Closed-Form Models of Accuracy Loss due to Subsampling in SVD Collaborative Filtering

Big data Mining and Analytics 2023年第1期6卷 72-84页

作者： Samin Poudel Marwan Bikdash Department of Computational Data Science and Engineering North Carolina A&T State UniversityGreensboroNC 27401USA

We postulate and analyze a nonlinear subsampling accuracy loss(SSAL)model based on the root mean square error(RMSE)and two SSAL models based on the mean square error(MSE),suggested by extensive preliminary *** SSAL models predict accuracy loss in terms of subsampling parameters like the fraction of users dropped(FUD)and the fraction of items dropped(FID).We seek to investigate whether the models depend on the characteristics of the dataset in a constant way across datasets when using the SVD collaborative filtering(CF)*** dataset characteristics considered include various densities of the rating matrix and the numbers of users and *** simulations and rigorous regression analysis led to empirical symmetrical SSAL models in terms of FID and FUD whose coefficients depend only on the data *** SSAL models came out to be multi-linear in terms of odds ratios of dropping a user(or an item)*** dropping ***,one MSE deterioration model turned out to be linear in the FID and FUD odds where their interaction term has a zero *** importantly,the models are constant in the sense that they are written in closed-form using the considered data characteristics(densities and numbers of users and items).The models are validated through extensive simulations based on 850 synthetically generated primary(pre-subsampling)matrices derived from the 25M MovieLens *** 460000 subsampled rating matrices were then simulated and subjected to the singular value decomposition(SVD)CF *** validation was conducted using the 1M MovieLens and the Yahoo!Music Rating *** models were constant and significant across all 3 datasets.

关键词： collaborative filtering subsampling accuracy loss models performance loss recommendation system simulation rating matrix root mean square error

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A Tutorial on Federated Learning from Theory to Practice:Foundations,Software Frameworks,Exemplary Use Cases,and Selected Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 824-850页

作者： M.Victoria Luzón Nuria Rodríguez-Barroso Alberto Argente-Garrido Daniel Jiménez-López Jose M.Moyano Javier Del Ser Weiping Ding Francisco Herrera Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of Communications Engineering University of the Basque Country(UPV/EHU)and also with TECNALIABasque Research&Technology Alliance(BRTA)Spain School of Information Science and Technology Nantong UniversityNantong 226019China

When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized *** allows ML models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third *** paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that have leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data *** virtue of FL,models can be learned from all such distributed data sources while preserving data *** aim of this paper is to provide a practical tutorial on FL,including a short methodology and a systematic analysis of existing software ***,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of FL,describing the main components of FL,from key elements to FL categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for FL deployment,devising a methodology to design a FL scenario,and providing exemplary cases of study with source code for different ML approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current FL *** ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of FL in practical applications.

关键词： data privacy distributed machine learning federated learning software frameworks

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A Graph-Assisted Digital-Twin-Driven Multiagent Shared Offloading for Internet of Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 17349-17363页

作者： Zahangir Alam, Md Rahman, Suryaia Asif Bin Khaled, Md Islam, Ashraful Jamalipour, Abbas Independent University Bangladesh Department of Computer Science and Engineering Center for Computational and Data Sciences Dhaka1229 Bangladesh The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Vehicular edge computing (VEC) allows vehicles to process part of the tasks locally at the network edge while offloading the rest of the tasks to a centralized cloud server for processing. A massive volume of tasks generated by the Internet of Vehicles (IoV) leads to buffer overflow that causes higher latency. Elevating latency, in turn, can increase network energy consumption. Both higher latency and energy consumption lead to a degradation of network performance. Therefore, VEC design requires a balance between latency and energy consumption tradeoff. To reduce overwhelming amount of offloading to edge servers, a cooperative cluster-based shared offloading strategy has been proposed in this work. We use digital twin technology in VEC for managing and adapting to environmental dynamic changes. Then, we leverage Lyapunov (Ly) optimization to transform the stochastic offloading problem into a more manageable deterministic form. Finally, we present a decentralized coordination graph (CG)-driven Ly-based multiagent deep deterministic policy gradient (CG-LyMADDPG) algorithm that trains agents toward energy efficient optimal offloading policy while maintaining queue stability at a maximum delay constraint. The experimental result shows that the proposed learning significantly outperforms the baseline algorithms for energy savings while maintain queue stability. © 2014 IEEE.

关键词： Stochastic systems

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Large language models design sequencedefined macromolecules via evolutionary optimization

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npj computational Materials 2024年第1期10卷 446-453页

作者： Wesley F.Reinhart Antonia Statt Department of Materials Science and Engineering Pennsylvania State UniversityUniversity Park16802 PAUSA Institute for Computational and Data Sciences Pennsylvania State UniversityUniversity Park16802 PAUSA Department of Materials Science and Engineering Grainger College of EngineeringUniversity of Illinois Urbana-ChampaignChampaign61801 ILUSA

We demonstrate the ability of a large language model to perform evolutionary optimization for materials ***’s Claude 3.5 model outperforms an active learning scheme with handcrafted surrogate models and an evolutionary algorithm in selecting monomer sequences to produce targeted morphologies in macromolecular *** pre-trained language models can potentially reduce the need for hyperparameter tuning while offering new capabilities such as *** model performs this task effectively with orwithout context about the task itself,but domain-specific context sometimes results in faster convergence to good ***,when this context is withheld,the model infers an approximate notion of the task(e.g.,calling it a protein folding problem).This work provides evidence of Claude 3.5’s ability to act as an evolutionary optimizer,a recently discovered emergent behavior of large language models,and demonstrates a practical use case in the study and design of soft materials.

关键词： offering evolutionary faster

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Developing an Autonomous Robotics System Utilizing Camera and IMU Fusion with PID-Based Path Correction 23

Developing an Autonomous Robotics System Utilizing Camera an...

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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Penumatcha, Harsha Jaiswal, Chandra P. Vegesana, Sasank Alhmoud, Issa W. Gokaraju, Balakrishna Computational Data Science & Engineering North Carolina A&t State University Greensboro United States

ISBN: (纸本)9798350374889

This paper proposes a robot equipped with an autonomous navigation system that integrates visual data from a camera and dynamic data from an Inertial Measurement Unit (IMU) to ensure precise lane following. The system consists of the following components: 1) A Logitech web camera that continuously captures and provides visual feedback about the surrounding environment, 2) An IMU that provides real- time information on the robot's position, orientation, and movement, 3) A Jetson NX Platform serving as the central processing unit to process the fused data in real-time, interpreting the camera feed to extract relevant features such as lane lines and processing the IMU data to determine the robot's current orientation, acceleration, and velocity, 4) and Proportional-Integral-Derivative (PID) Controller which receives the integrated data and continuously evaluates the robot's current position and movement against the desired path. Based on these evaluations, the PID controller dynamically adjusts the robot's steering angle to ensure it remains within the lane, correcting its path in realtime. This integration of IMU and camera data with PID control results in a robust and adaptive autonomous navigation system capable of reliable lane detection and navigation, providing the robot with effective autonomous driving capabilities. The system adapts to environmental changes, such as varying lighting conditions and road textures, by continuously updating its parameters to maintain optimal performance. Furthermore, the real-time feedback loop enables the robot to iteratively improve its navigation capabilities, ensuring stable and accurate lane following. © 2024 IEEE.

关键词： Three term control systems

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Optimization Models for Teaching Load Formation of University Teachers 1

Optimization Models for Teaching Load Formation of Universit...

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IEEE AITU: 1st International Student Conference: "Digital Generation", AITU 2024

作者： Chigambayeva, Diana Goryakin, Makar Batova, Polina Department of Computational and Data Science Astana IT University Astana Kazakhstan Depatment of Computer Engineering Astana IT University Astana Kazakhstan

ISBN: (纸本)9798350364378

Functional and mathematical models for the distribution of academic workload at the stage of preparing the educational process at a university are considered, which make it possible to largely determine the uniformity of teachers’ workload with various types of academic work when fulfilling the criteria and restrictions adopted for the distribution. ©2024 IEEE.

关键词： functional model mathematical model study load educational process educational work types of educational work

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Minimal Counters, Maximum Insight: Simplifying System Performance With HPC Clusters for Optimized Monitoring

IEEE Computer Architecture Letters

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IEEE Computer Architecture Letters 2025年第1期24卷 177-180页

作者： Shukla, Shubhi Singh, Abhijeet Chakraborty, Rajdeep Chakraborty, Anirban Rathod, Tejas Mumbaikar, Harshal Munigala, Manoj Kumar Madhusudhan, K.N. Mitra, Pabitra Mukhopadhyay, Debdeep Indian Institute of Technology Kharagpur Centre for Computational Data Sciences India Indian Institute of Technology Kharagpur Computer Science and Engineering Department India Intel Corporation Bangalore India

As computer systems become more complex, evaluating performance requires tracking various hardware performance counters that capture the system's internal activities. While these counters provide valuable insights, their growing number makes it challenging to identify the most relevant ones for performance analysis. In this paper, we investigate the correlation between performance counter values and overall system performance, while also exploring the inter-correlation between different counters. Our findings demonstrate that specific counters are strongly correlated with key performance metrics and that significant redundancy exists among counters. By leveraging these relationships, we propose a method for selecting a small, representative set of performance counters. This streamlined set can further be used to accurately predict performance score across various workloads and system configurations. © 2002-2011 IEEE.

关键词： Complex networks

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EMG-Based Hand Gesture Recognition Using Individual Sensors on Different Muscle Groups

EMG-Based Hand Gesture Recognition Using Individual Sensors ...

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2023 IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2023

作者： Challa, Koundinya Alhmoud, Issa W. Kamrul Islam, A.K.M. Gokaraju, Balakrishna North Carolina Agricultural and Technical State University Computational Data Science and Engineering Greensboro United States

ISBN: (纸本)9798350359527

In this study, we introduce a novel classifier for hand gesture recognition based on electromyography (EMG). Our approach utilizes individual EMG sensors placed on various parts of the hand to capture signals related to hand movements. We conducted experiments involving eight healthy subjects, who performed three distinct hand gestures, including complex movements such as flexing, lifting, and grabbing an object. The EMG signals were captured from four channels, and from the acquired data, we extracted eight time-domain features. These features were then used to construct classifiers for the three investigated hand gestures, employing both random forest (RF) and logistic regression (LR) machine learning algorithms. Our results indicate that the RF and the LR classifiers achieved mean accuracies of 0.966 and 0.94, respectively. The high accuracies achieved by our classifiers highlight their reliability and effectiveness in capturing and interpreting hand movements, which open new possibilities for intuitive and precise control systems. © 2023 IEEE.

关键词： Palmprint recognition

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Optimal Dependence of Performance and Efficiency of Collaborative Filtering on Random Stratified Subsampling

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Big data Mining and Analytics 2022年第3期5卷 192-205页

作者： Samin Poudel Marwan Bikdash Department of Computational Data Science and Engineering North Carolina A&T State UniversityGreensboroNC 27401USA

Dropping fractions of users or items judiciously can reduce the computational cost of Collaborative Filtering(CF)*** effect of this subsampling on the computing time and accuracy of CF is not fully understood,and clear guidelines for selecting optimal or even appropriate subsampling levels are not *** this paper,we present a Density-based Random Stratified Subsampling using Clustering(DRSC)algorithm in which the desired Fraction of Users Dropped(FUD)and Fraction of Items Dropped(FID)are specified,and the overall density during subsampling is ***,we develop simple models of the Training Time Improvement(TTI)and the Accuracy Loss(AL)as functions of FUD and FID,based on extensive simulations of seven standard CF algorithms as applied to various primary matrices from MovieLens,Yahoo Music Rating,and Amazon Automotive *** show that both TTI and a scaled AL are bi-linear in FID and FUD for all seven *** TTI linear regression of a CF method appears to be same for all *** simulations illustrate that TTI can be estimated reliably with FUD and FID only,but AL requires considering additional dataset *** derived models are then used to optimize the levels of subsampling addressing the tradeoff between TTI and AL.A simple sub-optimal approximation was found,in which the optimal AL is proportional to the optimal Training Time Reduction Factor(TTRF)for higher values of TTRF,and the optimal subsampling levels,like optimal FID/(1-FID),are proportional to the square root of TTRF.

关键词： Collaborative Filtering(CF) subsampling Training Time Improvement(TTI) performance loss Recommendation System(RS) collaborative filtering optimal solutions rating matrix

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Spectroscopy and molecule opacity investigation on excited states of SiS

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Chinese Physics B 2024年第5期33卷 381-387页

作者：李瑞吕浩男桑纪群刘晓华梁桂颖吴勇 College of Teacher Education Qiqihar UniversityQiqihar 161006China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China Department of Physics College of ScienceQiqihar UniversityQiqihar 161006China School of Data Science and Artificial Intelligence Jilin Engineering Normal UniversityChangchun 130052China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100084China

The SiS molecule,which plays a significant role in space,has attracted a great deal of attention for many *** to complex interactions among its low-lying electronic states,precise information regarding the molecular structure of SiS is *** obtain accurate information about the structure of its excited states,the high-precision multireference configuration interaction(MRCI)method has been *** method is used to calculate the potential energy curves(PECs)of the 18Λ–S states corresponding to the lowest dissociation limit of *** core–valence correlation effect,Davidson’s correction and the scalar relativistic effect are also included to guarantee the precision of the MRCI *** on the calculated PECs,the spectroscopic constants of quasi-bound and bound electronic states are calculated and they are in accordance with previous experimental *** transition dipole moments(TDMs)and dipole moments(DMs)are determined by the MRCI *** addition,the abrupt variations of the DMs for the 1^(5)Σ^(+)and 2^(5)Σ^(+)states at the avoided crossing point are attributed to the variation of the electronic *** opacity of SiS at a pressure of 100 atms is presented across a series of *** increasing temperature,the expanding population of excited states blurs the band boundaries.

关键词： SiS opacity excited state spectroscopic constant configuration interaction

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