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DTSTART;TZID=Europe/Stockholm:20210823T120000
DTEND;TZID=Europe/Stockholm:20210823T123000
DTSTAMP:20260524T202153
CREATED:20210710T194146Z
LAST-MODIFIED:20210710T194222Z
UID:3559-1629720000-1629721800@www.software-center.se
SUMMARY:Lunch seminar: Don’t let sample size stop your A/B experiments
DESCRIPTION:Most welcome to the next Software Center Brown Bag seminar which will be hosted by theme 4 (‘Customer Data and Ecosystem Driven Development’) on August 23rd\, 12:00 – 12:30. \nOur presenter is Yuchu Liu who is an industrial PhD student at Volvo Cars. \nPlease find the title and the abstract of the talk below. Also\, attached to this e-mail are two recent papers by Yuchu in which she presents the research that works as the basis for this talk. \nAbstract:\nA/B testing is gaining attention in the automotive sector as a promising tool to measure casual effects from software changes. Different from the web-facing businesses where A/B testing is a well-established practice\, the automotive domain often suffers from limited eligible users to participate in online experiments. To address this shortcoming\, this talk describes how to run A/B testing with small sample sizes. In particular\, the talk presents a method for designing balanced control and treatment groups so that sound conclusions can be drawn from experiments with small sample sizes. Based on case study research with companies in the automotive domain\, the talk identifies the benefits and limitations of the A/B group design method. \n_______________________________________________ \nPlease help us forward this invite to your colleagues if you feel that this talk might be in their interest! \nWe look forward to meet with you at the Brown Bag seminar series in August – and until then we wish all of you a very nice summer! \n  \nRegards\,\nHelena \n_________________________________ \nMicrosoft Teams meeting \nJoin on your computer or mobile app \nClick here to join the meeting \nOr call in (audio only) \n+46 8 505 252 11\,\,876677862#   Sweden\, Stockholm \nPhone Conference ID: 876 677 862# \nFind a local number | Reset PIN \nLearn More | Meeting options \n________________________________________________________________________________ \n— Sc_bb mailing list Sc_bb@lists.chalmers.se https://lists.chalmers.se/mailman/listinfo/sc_bb
URL:https://www.software-center.se/event/lunch-seminar-dont-let-sample-size-stop-your-a-b-experiments/
LOCATION:Virtual event\, Sweden
CATEGORIES:Lunch seminar
ORGANIZER;CN="Helena Holmstr%C3%B6m Olsson":MAILTO:helena.holmstrom.olsson@mau.se
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DTSTART;TZID=Europe/Stockholm:20210830T120000
DTEND;TZID=Europe/Stockholm:20210830T123000
DTSTAMP:20260524T202153
CREATED:20210830T064133Z
LAST-MODIFIED:20210830T064133Z
UID:3655-1630324800-1630326600@www.software-center.se
SUMMARY:Lunch seminar: AI-Powered Fault Tolerance in Data Pipelines
DESCRIPTION:Welcome to the Software Center brown bag seminar organized by the AI engineering theme. The speaker is Aiswarya Raj\, PhD student at Chalmers. \nAbstract: A large volume of high-quality data is mission-critical for real-world AI applications. Data pipelines consolidate data from disparate sources into one common destination\, enable quick data accessibility\, and ensure consistent data quality\, which is crucial for AI applications. Companies from all domains experience data quality issues and practitioners report that they spend a significant amount of time in data pre-processing. Thus\, validating the quality of data is critical for establishing the trustworthiness of data pipelines\, but is mostly a challenging task of complex real-world applications. State-of-the-practice solutions require explicit domain expertise and are often implemented using a rule-based fault detection system. However\, due to the evolving nature of the data (data drifts)\, it is difficult to anticipate all faults associated with data that may occur in the data pipeline. Therefore\, in this talk\, the main focus will be on employing AI in the data pipeline for the detection of such faults and invoking corresponding mitigation strategies. We use a four-stage model to implement the AI-powered fault-tolerant data pipelines. From a research perspective\, the main benefit of the project is to enable companies to develop a data pipeline that delivers high-quality data products. To companies\, project results will help to reduce the amount of data pre-processing work done by data scientists\, data analysts and other AI practitioners while working with data\, which in turn accelerates the entire AI system development process. \n__________________________________________ \nMicrosoft Teams meeting \nJoin on your computer or mobile app \nClick here to join the meeting \nLearn More | Meeting options \n__________________________________________
URL:https://www.software-center.se/event/lunch-seminar-ai-powered-fault-tolerance-in-data-pipelines/
LOCATION:Virtual event\, Sweden
CATEGORIES:Lunch seminar
ORGANIZER;CN="Jan Bosch":MAILTO:jan.bosch@chalmers.se
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