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TZID:America/Detroit
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BEGIN:DAYLIGHT
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DTSTART:20070311T020000
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BEGIN:VEVENT
DTSTAMP:20260408T212122
DTSTART;TZID=America/Detroit:20261007T120000
DTEND;TZID=America/Detroit:20261007T130000
SUMMARY:Workshop / Seminar:AI Show and Tell
DESCRIPTION:
UID:142293-21890425@events.umich.edu
URL:https://events.umich.edu/event/142293
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260407T162632
DTSTART;TZID=America/Detroit:20261007T120000
DTEND;TZID=America/Detroit:20261007T123000
SUMMARY:Workshop / Seminar:King Talks Information Session
DESCRIPTION:These sessions will provide an overview of the application process\, expected time commitment\, and compensation associated with serving as a 2027 King Talks speaker.Interested individuals only need to attend one session.
UID:147511-21901161@events.umich.edu
URL:https://events.umich.edu/event/147511
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Rgs Events,Rgs-events,Sessions
LOCATION:Virtual via Zoom
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260407T162632
DTSTART;TZID=America/Detroit:20261007T150000
DTEND;TZID=America/Detroit:20261007T153000
SUMMARY:Workshop / Seminar:King Talks Information Session
DESCRIPTION:These sessions will provide an overview of the application process\, expected time commitment\, and compensation associated with serving as a 2027 King Talks speaker.Interested individuals only need to attend one session.
UID:147511-21901162@events.umich.edu
URL:https://events.umich.edu/event/147511
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Rgs Events,Rgs-events,Sessions
LOCATION:Virtual via Zoom
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260408T212127
DTSTART;TZID=America/Detroit:20261007T150000
DTEND;TZID=America/Detroit:20261007T170000
SUMMARY:Workshop / Seminar:RCRS Workshop A
DESCRIPTION:RCRS Workshop A: Appropriate citation of sources and avoiding plagiarism\; authorship and publication practices and responsibilities. \n
UID:147545-21901227@events.umich.edu
URL:https://events.umich.edu/event/147545
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:Johnson Rooms
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260407T124520
DTSTART;TZID=America/Detroit:20261007T160000
DTEND;TZID=America/Detroit:20261007T170000
SUMMARY:Workshop / Seminar:Robust and Risk-Sensitive Acceleration in Gradient Methods
DESCRIPTION:First-order methods such as gradient descent (GD) are foundational in optimization. In unconstrained problems with exact gradients\, momentum-based methods—most notably Nesterov’s accelerated gradient descent (AGD) and Polyak’s heavy-ball (HB) method—achieve faster convergence by improving dependence on the condition number. However\, this acceleration comes at a cost: momentum amplifies gradient noise\, making these methods less robust than GD under standard parameter choices and requiring more accurate gradient estimates to attain comparable accuracy. Similar challenges arise in convex and nonconvex min–max optimization.\nMotivated by applications in machine learning\, this talk studies unconstrained and min–max optimization under deterministic\, unbiased stochastic\, and biased stochastic gradient noise. I will present new algorithms that achieve optimal robustness against different noise types\, using control-theoretic tools such as the H_2​ norm\, the H_∞​ norm\, and the risk-sensitivity index\, together with coherent risk measures. I will also discuss worst-case noise constructions and high-probability convergence guarantees. This perspective builds a bridge between optimization and robust control theory and enables the design of noise-robust and risk-sensitive accelerated methods.\nRepresentative Publications:\nM. Gürbüzbalaban\, Y. Syed\, N. S. Aybat\, Accelerated gradient methods with biased gradient estimates: Risk sensitivity\, high-probability guarantees\, and large deviation bounds\, Journal of Nonlinear and Variational Analysis\, 2026 (Special Issue). https://jnva.biemdas.com/archives/2927\nM. Gürbüzbalaban\, Robustly Stable Accelerated Momentum Methods with a Near-Optimal L_2​ Gain and H_∞​ Performance\, Mathematics of Operations Research\, 2025.\nhttps://pubsonline.informs.org/doi/abs/10.1287/moor.2023.0321\nB. Can and M. Gürbüzbalaban\, Entropic risk-averse generalized momentum methods\, Optimization Methods and Software\, 2025. https://www.tandfonline.com/doi/abs/10.1080/10556788.2025.2549356
UID:141373-21888712@events.umich.edu
URL:https://events.umich.edu/event/141373
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
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