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DTSTART;TZID=Europe/Stockholm:20210201T120000
DTEND;TZID=Europe/Stockholm:20210201T123000
DTSTAMP:20260526T201258
CREATED:20201217T084633Z
LAST-MODIFIED:20210121T132151Z
UID:2464-1612180800-1612182600@www.software-center.se
SUMMARY:Lunch seminar: Privacy-aware machine learning method: Federated Learning
DESCRIPTION:Presenter: Hongyi Zhang\, PhD student\, Chalmers \nFederated Learning is an improved Machine Learning approach which enables edge devices to collaboratively learn a shared machine learning model. The data exchanged between the edge and central server are no longer user data but the updated model weights. Furthermore\, as this model training method is distributed\, there are chances to make the model become smarter and adapt to their environment. (For example\, devices in Malmö and Stockholm can have slightly different models based on their unique environment.) Due to the rapid increase of data collected on the edge\, it will become more expensive to gather data into a centralized server or cloud. Machine learning with distributed edge training will be the main approach for future AI engineering. This is also why Federated Learning is essential to industries. \nAdvantages of Federated Learning: \n\nPrivacy-Preserving\nNo need to send training data to a cloud or single server\nFast model deployment and evolution\nLow latency and efficient bandwidth utilization\n\nThere is a classic deployment from Google\, where they deployed Federated Learning in Gboard (A Mobile App) to collaboratively train models for improving keyboard query and predicting emoji. \nIn the software center\, we made close collaboration with industries. With Volvo Cars\, we validated Federated Learning in various industrial cases\, such as steering wheel angle prediction\, objective recognition\, etc. We have proved the efficiency of FL and further improved the technique by introducing asynchronous protocols for heterogeneous hardware settings in real-world cases. With Sahlgrenska University Hospital\, we are trying to help them estimate their resource allocation in a distributed manner and investigate the methods to continuously enhance the data privacy and security when applying machine learning in the medical health care field. \nAs the next step of our research\, we would like to investigate the possibility of Federated Learning with various industrial scenarios. We will try to adding autonomously improving mechanism into participated nodes to enhance the model quality and node autonomy. We are eager to collaborate with companies to help them accelerate and improve system autonomy of their machine learning procedure. \n__________________________________________________ \nMicrosoft Teams meeting \nJoin on your computer or mobile app\n \nClick here to join the meeting \n 
URL:https://www.software-center.se/event/lunch-seminar-ai-engineering-2/
LOCATION:Virtual event\, Sweden
ORGANIZER;CN="Jan Bosch":MAILTO:jan.bosch@chalmers.se
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210208T120000
DTEND;TZID=Europe/Stockholm:20210208T123000
DTSTAMP:20260526T201258
CREATED:20210121T121339Z
LAST-MODIFIED:20210217T155228Z
UID:2497-1612785600-1612787400@www.software-center.se
SUMMARY:Lunch seminar: Optimized Scheduling of Feature-Based Test Execution
DESCRIPTION:As test suites grow larger and more complex\, the time and resources required to execute the test suite also grows accordingly. This is particularly true for companies developing diverse product lines\, who must execute portions of the test suite on compatible hardware units with the features required by those test cases. We have recently begun to explore the topic of how to efficiently parallelize the execution of test cases across a pool of available hardware units. We propose a search-based test scheduling method that attempts to optimize the estimated execution time and utilization of the hardware pool. In this talk\, we will present our initial ideas\, the results from an early pilot study\, and our plans to integrate this approach into the test execution infrastructure at a Software Center partner company. \nSpeaker: Gregory Gay \nSlides \nAudio file
URL:https://www.software-center.se/event/optimized-scheduling-of-feature-based-test-execution/
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210215T120000
DTEND;TZID=Europe/Stockholm:20210215T123000
DTSTAMP:20260526T201258
CREATED:20210208T193453Z
LAST-MODIFIED:20210305T161448Z
UID:2509-1613390400-1613392200@www.software-center.se
SUMMARY:Lunch seminar: “There\, but what about Back Again? – Propagating manual modifications from generated code to the design model”
DESCRIPTION:Title: “There\, but what about Back Again? – Propagating manual modifications from generated code to the design model” \nSpeaker: Robbert Jongeling\, MDH \nAbstract:\nIn one of its forms\, model-based development brings the benefit of complete code generation from design models. The generated code may be subject to manual changes for several reasons\, such as fixing errors after code-level testing\, or adjusting the code for different variants of targeted hardware. As a consequence of these manual changes\, the consistency between the design model and code is likely lost. To ensure the maintainability of the model and code\, this consistency must be restored. In particular\, the manual changes to the generated code must be reflected in the design model too\, i.e.\, the model-code round-trip should be completed. In this talk\, we share our experiences of developing an approach and implementing a prototype solution for completing a model-code round-trip in an industrial setting where code generation is already established. \nLink to the recorded presentations >>
URL:https://www.software-center.se/event/lunch-seminar-there-but-what-about-back-again-propagating-manual-modifications-from-generated-code-to-the-design-model/
LOCATION:MS Teams
ORGANIZER;CN="Jan Carlson":MAILTO:jan.carlson@mdh.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20210223T090000
DTEND;TZID=Europe/Stockholm:20210223T100000
DTSTAMP:20260526T201258
CREATED:20201214T075215Z
LAST-MODIFIED:20201214T075215Z
UID:2389-1614070800-1614074400@www.software-center.se
SUMMARY:Coordination team meeting
DESCRIPTION:
URL:https://www.software-center.se/event/coordination-team-meeting-40/
LOCATION:Virtual event\, Sweden
ORGANIZER;CN="Jan Bosch":MAILTO:jan.bosch@chalmers.se
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