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Showing 1 to 20 of 101 for “"Machine Learning Applications"”.

  1. Quantum Machine Learning Applications and Algorithms

    L'abstract è presente nell'allegato / the abstract is in the attachment

    poli-torino Repository record for Quantum Machine Learning Applications and Algorithms (opens in a new tab)

  2. Machine Learning Applications For Neurological Diseases

    … or are collected from imperfect model systems. Machine learning approaches have proven helpful for processing these types of datasets and identifying relevant biological signal. In this thesis, I detail five examples of the utility of machine learning methods for analyzing neurological disease …

    mit Repository record for Machine Learning Applications For Neurological Diseases (opens in a new tab)

  3. SDEs and MFGs towards Machine Learning applications

    … investigation culminates in exploring pertinent Machine Learning methodologies applied to financial and economic decision-making processes.

    trento Repository record for SDEs and MFGs towards Machine Learning applications (opens in a new tab)

  4. Physically Motivated Feature Development for Machine Learning Applications

    … development forms a cornerstone of many machine learning applications. In this work, we develop features, motivated by physical or physiological knowledge, for several applications: energy disaggregation, brain cancer prognosis, and landmine detection with seismo-acoustic vibrometry …

    duke Repository record for Physically Motivated Feature Development for Machine Learning Applications (opens in a new tab)

  5. Machine learning applications for core guided petrophysical analysis

    … I present an analysis of several supervised learning algorithms to produce synthetic density and porosity logs using pressure-core data as ground truth and ultimately improve saturation estimation. Also, I apply an unsupervised learning algorithm to correlate the saturation estimation values …

    colo-mines Repository record for Machine learning applications for core guided petrophysical analysis (opens in a new tab)

  6. Machine Learning Applications in Structural Analysis and Design

    … science. In aerospace engineering, AI and machine learning (ML), a major branch of AI, are now playing an important role in various applications, such as automated systems, unmanned aerial vehicles, aerospace optimum design structure, etc. This dissertation mainly focuses on structural …

    vt Repository record for Machine Learning Applications in Structural Analysis and Design (opens in a new tab)

  7. Machine Learning Applications in Blockchain for Renewable Energy Systems

    … a synergistic framework that integrates advanced Machine Learning (ML) forecasting with Distributed Ledger Technology (DLT). The research first investigates the limits of predictive accuracy for community microgrids. A novel hybrid deep learning model, Bidirectional Long-Short-Term-Memory with …

    venda Repository record for Machine Learning Applications in Blockchain for Renewable Energy Systems (opens in a new tab)

  8. Automated deployment of machine learning applications to the cloud

    The use of machine learning (ML) as a key technology in artificial intelligence (AI) is becoming more and more important in the increasing digitalization of business processes. However, the majority of the development effort of ML applications is not related to the programming of the ML model, but …

    heid-thes Repository record for Automated deployment of machine learning applications to the cloud (opens in a new tab)

  9. In-situ Characterization and Machine Learning Applications for Composite Processing

    … leverages Digital Image Correlation (DIC) and Machine Learning Applications to effectively observe and track defect deformations occurring throughout the process. This process presents a dataset derived from the curing process of 40 carbon fiber-reinforced polymer (CFRP) samples within an …

    embry-riddle Repository record for In-situ Characterization and Machine Learning Applications for Composite Processing (opens in a new tab)

  10. Resource-efficient FPGA acceleration for machine learning applications through HLS

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01

    uiuc Repository record for Resource-efficient FPGA acceleration for machine learning applications through HLS (opens in a new tab)

  11. Smoothness and Adaptivity in Nonlinear Optimization for Machine Learning Applications

    … optimization has become the workhorse of machine learning. However, our theoretical understanding of optimization in machine learning is still limited. For example, classical optimization theory relies on assumptions like bounded Lipschitz smoothness of the loss function which are rarely …

    mit Repository record for Smoothness and Adaptivity in Nonlinear Optimization for Machine Learning Applications (opens in a new tab)

  12. Machine learning applications for the topology prediction of transmembrane beta-barrel proteins

    … play critical roles in the translocation machinery, pore formation, membrane anchoring, and ion exchange. In bioinformatics, many years of research have been spent on the topology prediction of transmembrane alpha-helices. The efforts to TMB (transmembrane beta-barrel) proteins topology …

    london-metro Repository record for Machine learning applications for the topology prediction of transmembrane beta-barrel proteins (opens in a new tab)

  13. Advances in Sparse and Low Rank Matrix Optimization for Machine Learning Applications

    … fundamental problems in operations research, machine learning, and statistics exhibit natural formulations as cardinality or rank constrained optimization problems. Sparse solutions are desirable for their interpretability and storage benefits. Moreover, in the machine learning setting, sparse …

    mit Repository record for Advances in Sparse and Low Rank Matrix Optimization for Machine Learning Applications (opens in a new tab)

  14. Performance analysis of machine learning applications on rapid: a highly parallel computer architecture

    … past few years, the interest and application of machine learning algorithms has risen exponentially. Machine learning has found extensive use in diverse fields like self-driving cars, speech recognition, image processing, computer vision, molecular biology, security etc. A lot of recent research …

    uiuc Repository record for Performance analysis of machine learning applications on rapid: a highly parallel computer architecture (opens in a new tab)

  15. Data Analytics and Machine Learning Applications in Fermentation Processes and Molecular Property Prediction

    Multivariate data analytics (MVDA) and machine learning (ML) have been playing a crucial role in bioprocesses and molecular property prediction. Our study encompasses three main aspects: 1) using data analytics to analyze the occurrence of foaming in batch fermentation processes using multiway …

    vt Repository record for Data Analytics and Machine Learning Applications in Fermentation Processes and Molecular Property Prediction (opens in a new tab)

  16. Artificial intelligence in business analytics, capturing value with machine learning applications in financial services

    … explores the strength and applicability of machine learning-based classifiers within the context of business analytics for data-driven decision making. The focus is on supervised binary classification on structured datasets, which are vastly present in relational databases across all …

    strathclyde Repository record for Artificial intelligence in business analytics, capturing value with machine learning applications in financial services (opens in a new tab)

  17. Enabling multi-scale sensing with wireless-informed machine learning: Applications in earth and space

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms

    uiuc Repository record for Enabling multi-scale sensing with wireless-informed machine learning: Applications in earth and space (opens in a new tab)

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