BEGIN:VCALENDAR
VERSION:2.0
PRODID:researchseminars.org
CALSCALE:GREGORIAN
X-WR-CALNAME:researchseminars.org
BEGIN:VEVENT
SUMMARY:Dr. Marly Gotti
DTSTART:20241016T000000Z
DTEND:20241016T010000Z
DTSTAMP:20260404T110745Z
UID:SimpleWords/1
DESCRIPTION:Title: <a href="https://stable.researchseminars.org/talk/Simpl
 eWords/1/">Harnessing the Power of Large Language Models in Mathematics: C
 urrent Trends and Future Directions</a>\nby Dr. Marly Gotti as part of Sim
 ple Words\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/SimpleWords/1/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Dr. Matthew Dallas (University of Dallas)
DTSTART:20241030T000000Z
DTEND:20241030T010000Z
DTSTAMP:20260404T110745Z
UID:SimpleWords/2
DESCRIPTION:Title: <a href="https://stable.researchseminars.org/talk/Simpl
 eWords/2/">Newton’s Method or: How to Solve Nonlinear Equations Fast</a>
 \nby Dr. Matthew Dallas (University of Dallas) as part of Simple Words\n\n
 Abstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/SimpleWords/2/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Prof. Anna Ma (University of California\, Irvine)
DTSTART:20241113T010000Z
DTEND:20241113T020000Z
DTSTAMP:20260404T110745Z
UID:SimpleWords/3
DESCRIPTION:Title: <a href="https://stable.researchseminars.org/talk/Simpl
 eWords/3/">Solving Large-Scale Linear Systems: From Gradient Descent to St
 ochastic Optimization in Data Science</a>\nby Prof. Anna Ma (University of
  California\, Irvine) as part of Simple Words\n\n\nAbstract\nIn applied ma
 thematics and data science\, we leverage our ability to access large amoun
 ts of data to make better decisions. While more data can provide more info
 rmation about the world around us\, working with large-scale data creates 
 new and interesting challenges. In this talk\, we will discuss these chall
 enges with respect to algorithmic approaches for a specific problem that o
 ften occurs in data science applications: solving large-scale linear syste
 ms.  We will explore a range of algorithmic approaches\, from classical me
 thods like Gradient Descent to more modern techniques such as Stochastic G
 radient Descent (SGD)\, highlighting how these methods are adapted to hand
 le the complexities of big data efficiently. By examining both traditional
  and cutting-edge algorithms\, we will provide insight into how numerical 
 techniques evolve to meet the demands of contemporary data-driven applicat
 ions.\n
LOCATION:https://stable.researchseminars.org/talk/SimpleWords/3/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Nathan Kaplan (UC Irvine)
DTSTART:20241211T010000Z
DTEND:20241211T020000Z
DTSTAMP:20260404T110745Z
UID:SimpleWords/4
DESCRIPTION:Title: <a href="https://stable.researchseminars.org/talk/Simpl
 eWords/4/">Error-Correcting Codes: The Mathematics of Communication</a>\nb
 y Nathan Kaplan (UC Irvine) as part of Simple Words\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/SimpleWords/4/
END:VEVENT
END:VCALENDAR