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X-ORIGINAL-URL:https://engineering.jhu.edu/ams
X-WR-CALDESC:Events for Department of Applied Mathematics and Statistics
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DTSTART;TZID=America/New_York:20221006T133000
DTEND;TZID=America/New_York:20221006T143000
DTSTAMP:20221002T182245
CREATED:20220920T142925Z
LAST-MODIFIED:20220921T193225Z
UID:43025-1665063000-1665066600@engineering.jhu.edu
SUMMARY:AMS Weekly Seminar w/ Anthony Yezzi (Georgia Tech) @ Shaffer 303 or Zoom
DESCRIPTION:Title: Accelerated Gradient Descent in the PDE Framework \nAbstract: \nFollowing the seminal work of Nesterov\, accelerated optimization methods (sometimes referred to as momentum methods) have been used to powerfully boost the performance of first-order\, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent\, but it performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration\, thereby selecting only local minimizers with a attraction basin large enough to accommodate the initial overshoot. This behavior has made accelerated search methods particularly popular within the machine learning community where stochastic variants have been proposed as well. Until recently\, however\, accelerated optimization methods have been applied to searches over finite parameter spaces. We show how a variational setting for these finite dimensional methods (published by Wibisono\, Wilson and Jordan in 2016) can be extended to the infinite dimensional setting\, both in linear functional spaces as well as to the more complicated manifold of 2D curves and 3D surfaces. Moreover\, we also show how extremely simple explicit discretizaion schemes can be used to efficiently solve the resulting class of high dimensional optimization problems. We will illustrate applications of this strategy to problems in image restortation\, image segmentation\, and 3D reconstruction. \nJoin via Zoom: \nhttps://wse.zoom.us/j/95738965246
URL:https://engineering.jhu.edu/ams/event/ams-weekly-seminar-w-anthony-yezzi-georgia-tech-shaffer-303-or-zoom/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221013T133000
DTEND;TZID=America/New_York:20221013T143000
DTSTAMP:20221002T182245
CREATED:20220920T143021Z
LAST-MODIFIED:20220927T152939Z
UID:43028-1665667800-1665671400@engineering.jhu.edu
SUMMARY:AMS Weekly Seminar w/ Victor Bailey (Georgia Tech) @ Shaffer 303 or Zoom
DESCRIPTION:Title: Frames via Unilateral Iterations of Bounded Operators \nAbstract: Dynamical Sampling is\, in a sense\, a hypernym classifying the set of inverse problems arising from considering samples of a signal and its future states under the action of a bounded linear operator. Recent works in this area consider questions such as when can a given frame for a separable Hilbert Space\, $\{f_k\}_{k \in I} \subset H$\, be represented by iterations of an operator on a single vector and what are necessary and sufficient conditions for a system\, $\{T^n \varphi\}_{n=0}^{\infty} \subset H$\, to be a frame? In this talk\, we will discuss the connection between frames given by iterations of a bounded operator and the theory of model spaces in the Hardy-Hilbert Space as well as necessary and sufficient conditions for a system generated by the orbit of a pair of commuting bounded operators to be a frame. \nJoin via Zoom: \nhttps://wse.zoom.us/j/95738965246
URL:https://engineering.jhu.edu/ams/event/ams-weekly-seminar-w-victor-bailey-georgia-tech-shaffer-303-or-zoom/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221027T133000
DTEND;TZID=America/New_York:20221027T143000
DTSTAMP:20221002T182245
CREATED:20220920T144745Z
LAST-MODIFIED:20220921T191642Z
UID:43083-1666877400-1666881000@engineering.jhu.edu
SUMMARY:AMS Weekly Seminar w/ Maria Cameron (UMD) @ Shaffer 303 or Zoom
DESCRIPTION:Title: TBA \nAbstract: TBA \nJoin via Zoom: \nhttps://wse.zoom.us/j/95738965246
URL:https://engineering.jhu.edu/ams/event/ams-weekly-seminar-w-maria-cameron-umd-shaffer-303-or-zoom/
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