Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 8 of 8 for “"Machine Learning Libraries"”.
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API Knowledge Guided Test Generation for Machine Learning Libraries
… MUTester to generate test cases for APIs of machine learning libraries by leveraging the API constraints mined from the corresponding API documentation and the API usage patterns mined from code fragments in Stack Overflow (SO). First, we propose a set of 18 linguistic rules for mining API …
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Converting PyTorch Models to StreamIt Pipelines
… models, there have been efforts to optimize machine learning inference to support a large volume of queries. Currently, the two main ways to do this are running optimized kernels for computing the forward inference pass and distributing computation across multiple GPUs or different cores in a …
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Privacy preserving framework for federated learning in genomics
With the advent of machine learning, organizations today collect and process data at an unprecedented scale. This has led to rapid growth in innovation across industries, but also poses numerous challenges around maintaining user privacy. Specifically, in the field of healthcare and genomics where …
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Mining Software Artifacts for use in Automated Machine Learning
Successfully implementing classical supervised machine learning pipelines requires that users have software engineering, machine learning, and domain experience. Machine learning libraries have helped along the first two dimensions by providing modular implementations of popular algorithms. …
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Broad-based side-channel defenses for modern microprocessors
… of cryptographic algorithms but also including machine-learning libraries, databases, and parsers. However, even after using techniques such as encryption, authentication, and isolation, it is difficult to maintain the privacy or confidentiality of such information due to so-called side …
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Collaborative, open, and automated data science
Data science and machine learning have already revolutionized many industries and organizations and are increasingly being used in an open-source setting to address important societal problems. However, there remain many challenges to developing predictive machine learning models in practice, such …
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Robust Statistical Radio Interferometric Methods for the Detection of the Epoch of Reionization
… more expensive, they can be accelerated with machine learning libraries and hardware. These robust techniques will become a cornerstone of radio astronomy on account of their ability to reduce large amounts of data with confidence and with little intervention.