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检索条件"机构=Mathematical Institute for Machine Learning and Data Science"
808 条 记 录,以下是1-10 订阅
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Structural Breakpoint Detection in Noisy Time Series Using an Augmented Matrix Profile Index  24
Structural Breakpoint Detection in Noisy Time Series Using a...
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24th IEEE International Conference on data Mining Workshops, ICDMW 2024
作者: Fuchs, Marco Catholic University of Eichstätt-Ingolstadt Mathematical Institute for Machine Learning and Data Science Ingolstadt Germany
We introduce a method for partitioning a time series into segments. The method extends the recently introduced Fast Low-Cost Semantic Segmentation (FLUSS) algorithm to increase its robustness against noise and to auto... 详细信息
来源: 评论
D’OH: Decoder-Only Random Hypernetworks for Implicit Neural Representations  17th
D’OH: Decoder-Only Random Hypernetworks for Implicit Neura...
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17th Asian Conference on Computer Vision, ACCV 2024
作者: Gordon, Cameron E. MacDonald, Lachlan Saratchandran, Hemanth Lucey, Simon Australian Institute for Machine Learning University of Adelaide AdelaideSA5000 Australia Mathematical Institute for Data Science John Hopkins University BaltimoreMD21218 United States
Deep implicit functions have been found to be an effective tool for efficiently encoding all manner of natural signals. Their attractiveness stems from their ability to compactly represent signals with little to no of... 详细信息
来源: 评论
Hybrid speech enhancement in modulation domain
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Multimedia Tools and Applications 2024年 1-31页
作者: P S, Praveen Kumar H S, Jayanna Technical Lead-Machine Learning Merit Data and Technology Tamil Nadu Chennai India Department of Information Science and Engineering Siddaganga Institute of Technology Karnataka Tumkur India
This paper presents a comprehensive study on speech enhancement (SE) techniques, particularly focusing on the utilization of the discrete cosine transform (DCT) in the modulation domain (MD) in combination with the mi... 详细信息
来源: 评论
Impact of Immersive Technology on Physiological Parameters in Psychiatric Disorders  13
Impact of Immersive Technology on Physiological Parameters i...
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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024
作者: Kataria, Anjali Singh, Gurjinder Sandhu, Jasminder Chitkara Institute of Engineering and Technology Punjab India Iilm University Department of Machine Learning and Data Science Noida India
The brain is an essential component that regulates the general functioning of the body. The brain consists of millions of neurons that govern human behavior in response to sensory stimuli. To understand the mental fun... 详细信息
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LSTM based Soft-Sensor for Estimating Nitrate Concentration in Aquaponics pond  3
LSTM based Soft-Sensor for Estimating Nitrate Concentration ...
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3rd International Conference for Innovation in Technology, INOCON 2024
作者: Dharshan, A. Kumar, Purushottam Ravimaran, S. Srinivasulu Reddy, U. Saranathan College of Engineering Department of Artificial Intelligence and Data Science Trichy India National Institute of Technology Artificial Intelligence Machine Learning & Data Analytics Lab Trichy India National Institute of Technology Department of Computer Applications Machine Learning & Data Analytics Lab Trichy India
In the field of aquaponics, where fish and plants coexist in a symbiotic environment, closely monitoring nitrate levels in the water is crucial due to their profound impact on aquatic and plant well-being. Traditional... 详细信息
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Improving Generalization and Convergence by Enhancing Implicit Regularization  38
Improving Generalization and Convergence by Enhancing Implic...
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Wang, Mingze Wang, Jinbo He, Haotian Wang, Zilin Huang, Guanhua Xiong, Feiyu Li, Zhiyu Weinan, E. Wu, Lei School of Mathematical Sciences Peking University China Center for Machine Learning Research Peking University China China AI for Science Institute China School of Data Science University of Science and Technology of China China ByteDance Research China
In this work, we propose an Implicit Regularization Enhancement (IRE) framework to accelerate the discovery of flat solutions in deep learning, thereby improving generalization and convergence. Specifically, IRE decou...
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Optimization of Random Feature Method in the High-Precision Regime
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Communications on Applied Mathematics and Computation 2024年 第2期6卷 1490-1517页
作者: Jingrun Chen Weinan E Yifei Sun School of Mathematical Sciences and Suzhou Institute for Advanced Research Suzhou 215006JiangsuChina University of Science and Technology of China Hefei 230026AnhuiChina Center for Machine Learning Research and School of Mathematical Sciences Peking UniversityBeijing 100871China AI for Science Institute Beijing 100084China School of Mathematical Sciences Soochow UniversitySuzhou 215006JiangsuChina
machine learning has been widely used for solving partial differential equations(PDEs)in recent years,among which the random feature method(RFM)exhibits spectral accuracy and can compete with traditional solvers in te... 详细信息
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Finding the transcription factor binding locations using novel algorithm segmentation to filtration (S2F)
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Journal of Ambient Intelligence and Humanized Computing 2024年 第9期15卷 3347-3358页
作者: Theepalakshmi, P. Srinivasulu Reddy, U. Department of Computer Science and Engineering Gandhi Institute of Technology and Management Karnataka Bengaluru India Machine Learning and Data Analytics Lab Center of Excellence in Artificial Intelligence Department of Computer Applications National Institute of Technology Tamilnadu Tiruchirappalli India
The primary aim of identifying the binding motifs in gene regulation is to understand the transcriptional regulation molecular mechanism systematically. In this study, the (, d) motif search issue was considered ... 详细信息
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Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling  38
Understanding the Expressive Power and Mechanisms of Transfo...
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Wang, Mingze Weinan, E. School of Mathematical Sciences Peking University Beijing China Center for Machine Learning Research School of Mathematical Sciences Peking University Beijing China AI for Science Institute Beijing China
We conduct a systematic study of the approximation properties of Transformer for sequence modeling with long, sparse and complicated memory. We investigate the mechanisms through which different components of Transfor...
来源: 评论
Sentiment Analysis on Real-Time Twitter data Using LSTM with Mutually Inclusive Classifiers  8th
Sentiment Analysis on Real-Time Twitter Data Using LSTM with...
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8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023
作者: Soumya, B.J. Swetha, B.N. Meeradevi, Ak. Kanavalli, Anita Shubhangi Singh, Yashashwini Anuritha, L. Singh, Anushka Department of Artificial Intelligence and Data Science Ramaiah Institute of Technology Bengaluru India Department of Artificial Intelligence and Machine Learning Ramaiah Institute of Technology Bengaluru India
A novel approach to perform sentiment analysis on real-time Twitter data using long short-term memory (LSTM) neural networks with mutually inclusive classifiers. The work leverages the vast amount of publicly availabl... 详细信息
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