检索结果-内蒙古大学图书馆

The Journal of Machine Learning Research 2023年第1期24卷 12974-13023页

作者： Aleksandr Beznosikov Samuel Horváth Peter Richtárik Mher Safaryan Computer Electrical and Math. Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal KSA and Skolkovo Institute of Science and Technology Moscow Russia and School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Moscow Russia Computer Electrical and Math. Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal KSA

In the last few years, various communication compression techniques have emerged as an indispensable tool helping to alleviate the communication bottleneck in distributed learning. However, despite the fact biased compressors often show superior performance in practice when compared to the much more studied and understood unbiased compressors, very little is known about them. In this work we study three classes of biased compression operators, two of which are new, and their performance when applied to (stochastic) gradient descent and distributed (stochastic) gradient descent. We show for the first time that biased compressors can lead to linear convergence rates both in the single node and distributed settings. We prove that distributed compressed SGD method, employed with error feedback mechanism, enjoys the ergodic rate $O\left( \delta L \exp[-\frac{\mu K}{\delta L}] + \frac{(C + \delta D)}{K\mu}\right)$, where δ ≥1 is a compression parameter which grows when more compression is applied, L and µ are the smoothness and strong convexity constants, C captures stochastic gradient noise (C = 0 if full gradients are computed on each node) and D captures the variance of the gradients at the optimum (D = 0 for over-parameterized models). Further, via a theoretical study of several synthetic and empirical distributions of communicated gradients, we shed light on why and by how much biased compressors outperform their unbiased variants. Finally, we propose several new biased compressors with promising theoretical guarantees and practical performance.

关键词： compression operators biased compressors distributed learning linear convergence error feedback

来源：评论

学校读者我要写书评

暂无评论

Cutting-Edge Predictive Methods for Enhancing Short-Term Load Prediction

Cutting-Edge Predictive Methods for Enhancing Short-Term Loa...

引用

2024 International Conference on Electrical and computer engineering Researches, ICECER 2024

作者： Ghazal, Taher M. Janjua, Jamshaid Iqbal Abushiba, Walid Ahmad, Munir Abbas, Tahir Ateeq, Karamath College of Arts & Science Applied Science University P.O.Box 5055 Manama Bahrain Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Selangor Malaysia Lahore Pakistan College of Engineering Applied Science University Bahrain College of Informatics Korea University Seoul02841 Korea Republic of TIMES Institute Department of Computer Science Multan Pakistan School of Computing Skyline University College University City Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798331539733

Efficient management and cost-related factors in the power sector call for accurate short-term load forecasting as it enables better planning with the electric grid and achieving stability within it. This paper looks into the state-of-the-art forecasting strategies that enhance load forecasts made in shorter time frames. Such techniques include but are not limited to machine learning applications, effective data models, and multi-dimensional modeling leveraging historical, meteorological, and economic data. Their review is carried out in detail with their advantages and disadvantages and their application in practice. Furthermore, this study strives to understand the barriers that need to be overcome in the quest to increase the accuracy of the forecasting models especially concerning renewable energy sources. We illustrate how new trends relate to future developments of predictive models about supporting the decision-making in operating power systems and improving the reliability and sustainability of energy systems. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

EEG Analysis of Human Perception based on Video-Audio Stimuli 1

EEG Analysis of Human Perception based on Video-Audio Stimul...

引用

1st International Conference on Smart Technologies Communication and Robotics, STCR 2021

作者： Manochitra, S. Partheepan, Ravinthiran Kalasalingam Institute of Technology Faculty of Computer Science and Engineering Tamilnadu Virudhunagar India Vytautas Magnus University Faculty of Informatics Master Programme - Applied Informatics Kaunas Lithuania

ISBN: (纸本)9781665418065

Emotions plays a potential role in human computer interaction which are having an obligatory models of cognitive measures. The emotions are dominated by the human physiological communication channels. Those emotions could affect several human activities like learning, decision making, communication, perception, cognitive and so on. Also, some of the emotions are quite difficult to measure and interpret and having difficulty in incorporating them into a technology and design. On the other hand, state of the technologies has enabled us to capture the emotions and integrate them for the use of human computer interaction contexts. This paper delivers an attempt to model the emotions using electroencephalography (EEG). The video stimuli for the two representatives are based on a few negative, positive and neutral contents were shown to volunteers and EEG data was obtained. Further, EEG analysis were experimented and collected about their emotional states with subject's self reports. This study determines that the human emotions could be modelled for affect assessment module or for the usage in human computer interaction and affect based intelligent interactions. © 2021 IEEE.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Observation of Su-Schrieffer-Heeger Topological Model Band Structure in Integrated LNOI Coupled Ring Cavities 16

Observation of Su-Schrieffer-Heeger Topological Model Band S...

引用

16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Dinh, Hiep X. Balcytis, Armandas Ozawa, Tomoki Ota, Yasutomo Baba, Toshihiko Iwamoto, Satoshi Mitchell, Arnan Nguyen, Thach G. Rmit University Integrated Photonics and Applications Centre MelbourneVIC3000 Australia Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan Keio University Department of Applied Physics and Physico-Informatics Yokohama223-8522 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan The University of Tokyo Research Center for Advanced Science and Technology Tokyo153-8904 Japan

We report synthetic frequency dimension Su-Schrieffer-Heeger model and its band structure observation using coupled ring cavities on an integrated photonic chip. Intra-cell and inter-cell couplings between hybridized ... 详细信息

ISBN: (纸本)9798350372076

关键词： Photonic integrated circuits

来源：评论

学校读者我要写书评

暂无评论

Multiclass skin lesion classification using deep learning networks optimal information fusion

引用

Discover applied Sciences 2024年第6期6卷 1-13页

作者： Khan, Muhammad Attique Hamza, Ameer Shabaz, Mohammad Kadry, Seifeine Rubab, Saddaf Bilal, Muhammad Abdullah Akbar, Muhammad Naeem Kesavan, Suresh Manic Department of Computer Science HITEC University Taxila Pakistan Model Institute of Engineering and Technology Jammu India Department of Applied Data Science Noroff University College Oslo Norway Department of Computer Engineering College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of CS SEECS NUST Islamabad Pakistan National University of Sciences and Technology (NUST) Islamabad Pakistan Department of Electrical and Communication Engineering National University of Science and Technology Muscat Sultanate of Oman

A serious, all-encompassing, and deadly cancer that affects every part of the body is skin cancer. The most prevalent causes of skin lesions are UV radiation, which can damage human skin, and moles. If skin cancer is discovered early, it may be adequately treated. In order to diagnose skin lesions with less effort, dermatologists are increasingly turning to machine learning (ML) techniques and computer-aided diagnostic (CAD) systems. This paper proposes a computerized method for multiclass lesion classification using a fusion of optimal deep-learning model features. The dataset used in this work, ISIC2018, is imbalanced; therefore, augmentation is performed based on a few mathematical operations. After that, two pre-trained deep learning models (DarkNet-19 and MobileNet-V2) have been fine-tuned and trained on the selected dataset. After training, features are extracted from the average pool layer and optimized using a hybrid firefly optimization technique. The selected features are fused in two ways: (i) original serial approach and (ii) proposed threshold approach. Machine learning classifiers are used to classify the chosen features at the end. Using the ISIC2018 dataset, the experimental procedure produced an accuracy of 89.0%. Whereas, 87.34, 87.57, and 87.45 are sensitivity, precision, and F1 score respectively. At the end, comparison is also conducted with recent techniques, and it shows the proposed method shows improved accuracy along with other performance measures.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MassSpecGym: A benchmark for the discovery and identification of molecules 38

MassSpecGym: A benchmark for the discovery and identificatio...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Bushuiev, Roman Bushuiev, Anton de Jonge, Niek F. Young, Adamo Kretschmer, Fleming Samusevich, Raman Heirman, Janne Wang, Fei Zhang, Luke Dührkop, Kai Ludwig, Marcus Haupt, Nils A. Kalia, Apurva Brungs, Corinna Schmid, Robin Greiner, Russell Wang, Bo Wishart, David S. Liu, Li-Ping Rousu, Juho Bittremieux, Wout Rost, Hannes Mak, Tytus D. Hassoun, Soha Huber, Florian van der Hooft, Justin J.J. Stravs, Michael A. Böcker, Sebastian Sivic, Josef Pluskal, Tomáš Institute of Organic Chemistry and Biochemistry The Czech Academy of Sciences Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Czech Republic Bioinformatics Group Wageningen University & Research Netherlands Department of Computer Science University of Toronto Canada Bioinformatics Institute for Computer Science Friedrich Schiller University Jena Germany Department of Computer Science University of Antwerp Belgium Department of computing science University of Alberta Canada Alberta Machine Intelligence Institute Canada Department of Molecular Genetics University of Toronto Canada Bright Giant GmbH Department of Computer Science Tufts University United States Department of Biological Sciences University of Alberta Canada Department of Computer Science Aalto University Finland Mass Spectrometry Data Center National Institute of Standards and Technology United States Department of Chemical and Biological Engineering Tufts University United States Centre for Digitalisation and Digitality University of Applied Sciences Düsseldorf Germany Department of Biochemistry University of Johannesburg South Africa Eawag Swiss Federal Institute of Aquatic Science and Technology Switzerland

The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is the leading technique for high-throughput elucidation of molecular structures. However, decoding a molecular structure from its mass spectrum is exceptionally challenging, even when performed by human experts. As a result, the vast majority of acquired MS/MS spectra remain uninterpreted, thereby limiting our understanding of the underlying (bio)chemical processes. Despite decades of progress in machine learning applications for predicting molecular structures from MS/MS spectra, the development of new methods is severely hindered by the lack of standard datasets and evaluation protocols. To address this problem, we propose MassSpecGym - the first comprehensive benchmark for the discovery and identification of molecules from MS/MS data. Our benchmark comprises the largest publicly available collection of high-quality labeled MS/MS spectra and defines three MS/MS annotation challenges: de novo molecular structure generation, molecule retrieval, and spectrum simulation. It includes new evaluation metrics and a generalization-demanding data split, therefore standardizing the MS/MS annotation tasks and rendering the problem accessible to the broad machine learning community. MassSpecGym is publicly available at https://***/pluskal-lab/MassSpecGym. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Discrete control algorithms for systems with big dead time for control101 MATLAB toolbox

Discrete control algorithms for systems with big dead time f...

引用

Cybernetics & informatics (K&I)

作者： Ruth Bars Gyula Max J. Anthony Rossiter László Keviczky Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary School of Electrical and Electronic Engineering University of Sheffield Sheffield UK Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

ISBN: (数字)9798331541811

ISBN: (纸本)9798331541828

The first course of control is under a critical review. Both the teaching material covered and the teaching methods require new considerations. Introducing interactivity in the education process makes the learning more successful and enjoyable. MATLAB provides an effective environment for learning and applying different disciplines. Control101 is a new MATLAB toolbox under development which provides tools for interactive learning of control disciplines. This paper presents the framework for teaching discrete control algorithms applied for processes containing large dead times.

关键词： Visualization Systematics PI control Reviews Education Laboratories Process control Prediction algorithms PD control MATLAB

来源：评论

学校读者我要写书评

暂无评论

Influence of structural defects on charge density waves in 1T-TaS_(2)

引用

Nano Research 2023年第8期16卷 11528-11539页

作者： Iaroslav Lutsyk Karol Szalowski Pawel Krukowski Pawel Dabrowski Maciej Rogala Witold Kozlowski Maxime Le Ster Michal Piskorski Dorota A.Kowalczyk Wojciech Rys Rafal Dunal Aleksandra Nadolska Klaudia Toczek Przemyslaw Przybysz Ewa Lacinska Johannes Binder Andrzej Wysmolek Natalia Olszowska Jacek J.Kolodziej Martin Gmitra Takuma Hattori Yuji Kuwahara Guang Bian Tai-Chang Chiang Pawel J.Kowalczyk Faculty of Physics and Applied Informatics University of LodzPomorska 149/15390-236 LodzPoland Faculty of Physics University of WarsawPasteura 502-093 WarsawPoland Faculty of Physics Astronomyand Applied Computer ScienceJagiellonian UniversityLojasiewicza 1130-348 KrakowPoland National Synchrotron Radiation Centre SOLARIS Jagiellonian UniversityCzerwone Maki 9830-392 KrakówPoland Institute of Physics Faculty of SciencePavol JozefŠafárik University in KošicePark Angelinum 904001 KošiceSlovakia Institute of Experimental Physics Slovak Academy of SciencesWatsonova 4704001 KošiceSlovakia Department of Precision Engineering Graduate School of EngineeringOsaka University2-1 Yamada-okaSuita 565-0871Japan Department of Physics and Astronomy University of MissouriColumbiaMissouri 65211USA Department of Physics and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana-ChampaignUrbanaIllinois 61801-3080USA

The influence of intrinsic defects of 1T-TaS_(2)on charge density waves(CDWs)is studied using scanning tunneling microscopy and spectroscopy(STM,STS),angle-resolved photoelectron spectroscopy(ARPES),and density functional theory(DFT).We identify several types of structural defects and find that most have a local character limited to a single CDW site,with a single exception which effectively behaves as a dopant,leading to band-bending and affecting multiple neighboring *** only one type of defect can be observed by STM topographic imaging,all defects are easily resolved in STS *** results indicate modulation of the Mott band gap commensurate with the CDW and breaking of the three-fold symmetry of electronic *** calculations(with included Coulomb interactions)are used to investigate the electronic structure,focusing on both sulfur vacancy and oxygen-sulfur *** sulfur vacancy system,characterized with a metallic behavior,is identified as the origin of one of the experimentally observed ***,the effect of oxidation of 1T-TaS_(2)depends on the substitution site,leading to the heterogeneity of electronic properties.

关键词： structural charge sulfur

来源：评论

学校读者我要写书评

暂无评论

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

引用

Financial Innovation 2023年第1期9卷 2939-2991页

作者： Zhen‑Song Chen Jia Zhou Chen‑Ye Zhu Zhu‑Jun Wang Sheng‑Hua Xiong Rosa M.Rodríguez Luis Martínez Mirosław J.Skibniewski School of Civil Engineering Wuhan UniversityWuhan 430072China College of Civil Aviation Safety Engineering Civil Aviation Flight University of ChinaGuanghan 618307China School of Management Xi’an Jiaotong UniversityXi’an 710049China Department of Computer Science University of Jaén23071 JaénSpain Department of Civil and Environmental Engineering University of MarylandCollege ParkMD 20742‑3021USA Institute for Theoretical and Applied Informatics Polish Academy of SciencesGliwicePoland Chaoyang University of Technology TaizhongTaiwan

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and *** the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment ***,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate ***,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment *** improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making ***,a credit risk assessment index for Chinese real estate enterprises is ***,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II *** approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation ***,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and *** study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

关键词： Real estate enterprise Credit risk assessment PROMETHEE II Best–worst method Proportional hesitant fuzzy linguistic term sets

来源：评论

学校读者我要写书评

暂无评论

Promoting Accurate Image Reconstruction via Synthetic Noise for Unsupervised Screw Anomaly Detection and Location

引用

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Chen, Jian Wen Lin, Wan Ju Li, Kuan Ming Mrozek, Dariusz Hung, Che Lun National Tsing Hua University Department of Computer Science Hsinchu300044 Taiwan National Kaohsiung University of Science and Technology Department of Mold and Die Kaohsiung80778 Taiwan National Taiwan University Department of Mechanical Engineering Taipei106319 Taiwan Silesian University of Technology Department of Applied Informatics Poland National Yang Ming Chiao Tung University Institute of Biomedical Informatics Taipei11221 Taiwan

With residuals-based unsupervised models, defects can be detected using only normal samples, boosting both efficiency and practicality in industrial anomaly detection (AD) applications. While these approaches offer benefits, they also present challenges in detecting anomalies in cylindrical objects, such as imprecise image reconstruction and camera blind spots. As a result, this paper introduces ScrewNet, an unsupervised anomaly detection framework designed specifically for cylindrical objects like screws. To improve the accuracy of reconstruction in the AD network, the synthetic noise module and pair training approach are employed during the training stage. The synthetic noise module, utilizing one of the CycleGAN generators, produces defects that match real-world distributions, thereby enabling the AD network to extract valuable features while preserving image structure. The pair training approach is designed to enable the AD network to achieve accurate reconstruction using similar background input-output pairs. To tackle inspection blind spots problem, an efficient, cost-effective inspection system using multiple mirrors is developed for the inference stage. This approach enables effective anomaly detection across the entire 360-degree surface of the screw. In experiments, three different types of screw datasets containing both damaged and undamaged screws are provided. Numerous experiments demonstrate the superiority of our approach over several state-of-the-art (SOTA) unsupervised AD networks. For instance, ScrewNet outperforms baselines by 4 dB in average Peak signal-to-noise ratio (PSNR) for image reconstruction quality and by 32% in average Area Under the Receiver Operating Characteristic curve (AUROC) for pixel-level anomaly segmentation. Additionally, image-level detection achieves 98.3% accuracy across the three screw datasets. The code is available at https://***/vitowen9580/ScrewNet. © 2025 IEEE.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：