[UCR_DataScience] REMINDER: Data Science talk by Prof. Eamonn Keogh, tomorrow Friday September 30th, 12-1pm, MRB Seminar Room

[Vassilis Tsotras]

Reminder about the Data Science Seminar by Prof. Eamonn Keogh, tomorrow
Friday at noon.

Please register using the link below if you plan to attend.

V. Tsotras

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On 9/23/22 4:39 PM, tsotras at cs.ucr.edu wrote:
> The Data Science seminars for Fall 2022 start next Friday, September 30th,
> 2022.
> The seminar takes place 12:00-1:00pm at the MRB Seminar Room (1st floor).
>
> **** Pizza and refreshments will be provided ****
>
> To keep track of the number of attendees, please *register* at:
> https://www.eventbrite.com/e/data-science-talk-tickets-425985081847
>
> The talk will be given by Eamonn Keogh, Distinguished Professor,
> Department of Computer Science and Engineering, UCR
>
> Title:
> Why 95% of papers on Time Series Anomaly Detection are Wrong (with more
> general lessons for Researchers).
>
> Abstract:
>
> Time Series Anomaly Detection (TSAD) is the task of monitoring a time
> series, say an ECG, or the pressure in an industrial boiler, while
> attempting to recognize when there has been an anomalous event. The
> anomalies could be the beginning of heart attack, or a leak in the boiler
> that will cause the industrial product to spoil. TSAD is a commercially
> important problem, by most estimates worth billions of dollars each year.
> In the last few years there has been an explosion of interest in TSAD,
> with dozens of papers appearing in the top conferences and journals each
> year.
>
> In this talk I will make a surprising claim. At least 95% of the papers on
> TSAD are deeply flawed, and are at best unreliable. These flaws come from
> two major sources, using unsuitable metrics of success, and testing on
> flawed benchmark datasets. I will demonstrate my claims with forcefully,
> simple, visual examples. I will then go on to suggest some simple fixes
> for these issues. I will conclude by briefly touching on two interesting
> meta-questions. How did the research community not spot these issues
> before? And, what does it say that when these issues are pointed out, most
> of the community offers no counterarguments, but just ignores the problem
> (the head-in-the-sand response).
>
> Joint work with Renjie Wu.
>
>
> ------------------------------------
> Sponsored by the UCR Data Science Center, the purpose of the Data Science
> talks is to foster collaborations between "core" Data Science faculty
> (from CSE/ECE/Stat Departments) and faculty/visitors from other sciences
> that face Data Science problems in their research. These informal
> gatherings are open to interested faculty and graduate students. Each
> meeting will start with a talk describing research problems and then a
> discussion will follow for questions, open problems, ideas for possible
> collaborations etc.
>
> A full list of previous seminars appears at:
> http://datascience.ucr.edu/seminars
>
> Please forward this email to other colleagues or graduate students in your
> lab that may be interested.
>
> Moreover, if you are interested in giving a Data Science related talk,
> please contact me.
>
> Sincerely,
> Vassilis Tsotras
> Professor, CSE Department
> Director, Data Science Major
>
>
>
>
>
>
>
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