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Showing 1 to 20 of 161 for “"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

    … 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 data. …

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

  3. Optimizing Systems for Deep Learning Applications

    Modern systems for Machine Learning (ML) workloads support heterogeneous workloads and resources. However, existing resource managers in these systems do not differentiate between heterogeneous GPU resources. Moreover, users are usually unaware of the sufficient and appropriate type and amount of …

    vt Repository record for Optimizing Systems for Deep Learning Applications (opens in a new tab)

  4. Unsupervised Relation Extraction for E-Learning Applications

    … and business organisations are adopting the e-Learning approach as it provides an effective method for educating and testing their students and staff. The continuous development in the area of information technology and increasing use of the internet has resulted in a huge global market and …

    wlv Repository record for Unsupervised Relation Extraction for E-Learning Applications (opens in a new tab)

  5. SDEs and MFGs towards Machine Learning applications

    … 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)

  6. 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 (SAVi) …

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

  7. 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)

  8. Machine Learning Applications in Structural Analysis and Design

    … 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 engineering …

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

  9. Machine Learning Applications in Blockchain for Renewable Energy Systems

    … 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 Gated …

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

  10. 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)

  11. Boolean algebra: from digital circuits to deep learning applications

    … utilizações inovadoras, como no campo do deep learning. Esta aplicação permite desenvolver modelos computacionalmente eficientes e avançar o estado da arte em áreas como sistemas embebidos e computação de baixa potência. A dissertação analisa em profundidade a álgebra de Boole, examinando as …

    aberta Repository record for Boolean algebra: from digital circuits to deep learning applications (opens in a new tab)

  12. Acceleration of deep learning applications for astrophysics on FPGAs

    The student, Mengshen Yun, accepted the attached license on 2021-12-09 at 10:48.

    uiuc Repository record for Acceleration of deep learning applications for astrophysics on FPGAs (opens in a new tab)

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

    … 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 autoclave. …

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

  14. 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)

  15. 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 met in …

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

  16. CHATTER : a spoken language dialogue system for language learning applications

    … thesis is to build a Computer Aided Language Learning game that simulates a casual conversation in Mandarin Chinese. In the envisioned system, users will chat with a computer on topics ranging from relationship status to favorite Chinese dish. I hope to provide learners with more opportunities …

    mit Repository record for CHATTER : a spoken language dialogue system for language learning applications (opens in a new tab)

  17. Towards a Resource Efficient Framework for Distributed Deep Learning Applications

    Distributed deep learning has achieved tremendous success for solving scientific problems in research and discovery over the past years. Deep learning training is quite challenging because it requires training on large-scale massive dataset, especially with graphics processing units (GPUs) in …

    vt Repository record for Towards a Resource Efficient Framework for Distributed Deep Learning Applications (opens in a new tab)

  18. FROM FAMILY INTERACTION TO DYNAMIC FEEDBACK:ADVANCES IN MANDARIN LANGUAGE LEARNING APPLICATIONS

    … training remains underrepresented in learning. This thesis covers two Computer-Assisted Language Learning (CALL) projects enhancing Mandarin acquisition. The first focuses on a tablet app for children and parents, using Automatic Speech Evaluation (ASE) to give phoneme and tone …

    nus Repository record for FROM FAMILY INTERACTION TO DYNAMIC FEEDBACK:ADVANCES IN MANDARIN LANGUAGE LEARNING APPLICATIONS (opens in a new tab)

  19. Acceleration of deep learning applications using Intel distribution of OpenVINO toolkit

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

    uiuc Repository record for Acceleration of deep learning applications using Intel distribution of OpenVINO toolkit (opens in a new tab)

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