Machine learning testing

• [PDF File]Group Testing in a Pandemic: The Role of Frequent Testing ...

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  Group Testing in a Pandemic: The Role of Frequent Testing, Correlated Risk, and Machine Learning Ned Augenblick, Jonathan Kolstad, Ziad Obermeyer, Ao Wang UC Berkeley July 17, 2020 Abstract Group testing increases e ciency by pooling patient specimens, such that an entire group can be cleared with one negative test.

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• [PDF File]Predicting Metamorphic Relations for Testing Scientific ...

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  Predicting Metamorphic Relations for Testing Scientific Software: A Machine Learning Approach Using Graph Kernels Upulee Kanewala , James M. Bieman, and Asa Ben-Hur Computer Science Department, Colorado State University, USA SUMMARY Comprehensive, automated software testing requires an oracle to check whether the output produced by a

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• [PDF File]Testing machine learning based systems: a systematic mapping

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  nario/input generation and test oracle creation. MLS testing is a rapidly growing and developing research area, with many open challenges, such as the generation of realistic inputs and the definition of reliable evaluation metrics and benchmarks. Keywords Systematic mapping · Systematic review · Software testing · Machine learning

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• [PDF File]The ML Test Score: A Rubric for ML Production Readiness ...

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  Software testing is well studied, as is machine learning, but their intersection has been less well explored in the literature. [4] reviews testing for scientific software more generally, and cites a number of articles such as [5], who present an approach for testing ML algorithms. These ideas are a useful complement for the tests we present ...

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• APPLICATION OF MACHINE LEARNING IN DIGITAL LOGIC …

  2. Preparation of VLSI testing data and feature selection according to the ML model 3. Create an ML model to predict the behavior of a circuit by giving truth table of a circuit 4. Training, and testing of machine learning model for high accuracy.

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• [PDF File]AppFlow: Using Machine Learning to Synthesize …

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  complete regression testing. A key idea in AppFlow is a machine learning approach to recog-nizing screens and widgets. Instead of relying on developers’ hard-coded logic, AppFlow learns a classifier from a training dataset of screens and widgets labeled with their intents, using a careful se-

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• [PDF File]Applications of Machine Learning for Autonomous Driving ...

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  Jan 11, 2018 · How to Expedite Learning and Testing? • Practices of Safety Assurance Testing: • Learn from database of “corner cases” • Collection of challenging scenarios and probable test cases for specifications • “Fleet” Learning • Tesla, e.g. • “Simulated” Learning • Waymo, e.g.

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• [PDF File]Machine Learning-based Software Testing: Towards a ...

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  module testing, unit testing, and regression testing, which refer to requirement analysis, architectural design, subsystem design, detailed design, implementation, and maintenance in the software development stages, respectively. Dimension 4-Learning technique: In the machine learning area, various types of learning methods have been introduced

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• AUTOMATED TESTING AND MACHINE-LEARNING-BASED …

  AUTOMATED TESTING AND MACHINE-LEARNING-BASED MODELING OF AIR DISCHARGE ESD BY SAM SAGAN THESIS Submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Computer Engineering in the Graduate College of the University of Illinois at Urbana-Champaign, 2017 Urbana, Illinois Adviser:

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• [PDF File]Methods Research Report: Testing a Machine Learning Tool ...

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  Testing a Machine Learning Tool for Facilitating Living Systematic Reviews of Chronic Pain Treatments. Methods Research Report. (Prepared by the Pacific Northwest Evidence-based Practice Center under Contract No. 290-2015-00009-I and the Southern California Evidence-based …

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