Accelerated reconstruction of a compressively sampled data streamPantelis Sopasakis
Recursive compressed sensing on a stream of data: The traditional compressed sensing approach is naturally offline, in that it amounts to sparsely sampling and reconstructing a given dataset. Recently, an online algorithm for performing compressed sensing on streaming data was proposed: the scheme uses recursive sampling of the input stream and recursive decompression to accurately estimate stream entries from the acquired noisy measurements.
In this paper, we develop a novel Newton-type forward-backward proximal method to recursively solve the regularized Least-Squares problem (LASSO) online. We establish global convergence of our method as well as a local quadratic convergence rate. Our simulations show a substantial speed-up over the state of the art which may render the proposed method suitable for applications with stringent real-time constraints.
Accelerated reconstruction of a compressively sampled data streamPantelis Sopasakis
Recursive compressed sensing on a stream of data: The traditional compressed sensing approach is naturally offline, in that it amounts to sparsely sampling and reconstructing a given dataset. Recently, an online algorithm for performing compressed sensing on streaming data was proposed: the scheme uses recursive sampling of the input stream and recursive decompression to accurately estimate stream entries from the acquired noisy measurements.
In this paper, we develop a novel Newton-type forward-backward proximal method to recursively solve the regularized Least-Squares problem (LASSO) online. We establish global convergence of our method as well as a local quadratic convergence rate. Our simulations show a substantial speed-up over the state of the art which may render the proposed method suitable for applications with stringent real-time constraints.
Presented and prepared for AMA-Richmond Social Media SIG held on April 22, 2010. AMA is American Marketing Association of Richmond VA. SIG is special interest group.
Presented by Sally Witzky, Chief Social Media Strategist for Traction Group, a social media marketing agency in Richmond VA.
Sources for charts: SAI, TechCrunch, Mashable, etc. Please refer to the owners for further information.
This presentation was produced simply to give an overview of the current State of the Union of social media based on industry sources.
Am Freitag, 27. April 2012, war Tonio Grawe in ConSol’s Webcast als Gastredner zu dem Thema Agilität im Projektmanagement. Tonio Grawe: “Meine These ist, dass die Innovationskraft von Projekten deutlich gestärkt werden kann, wenn man die agile Denkweise, wie sie im Agile Manifesto definiert ist, bei der Führung solcher Vorhaben zugrunde legt.”
Sehen Sie den Webcast hier an:
http://advicio.com/2012/04/agilitaet_im_projektmanagement_innovation_ist_kein_zufall/
Distributed solution of stochastic optimal control problem on GPUsPantelis Sopasakis
Stochastic optimal control problems arise in many
applications and are, in principle,
large-scale involving up to millions of decision variables. Their
applicability in control applications is often limited by the
availability of algorithms that can solve them efficiently and within
the sampling time of the controlled system.
In this paper we propose a dual accelerated proximal
gradient algorithm which is amenable to parallelization and
demonstrate that its GPU implementation affords high speed-up
values (with respect to a CPU implementation) and greatly outperforms
well-established commercial optimizers such as Gurobi.
Distributed solution of stochastic optimal control problem on GPUs
презентациягороховцева
1.
2. Наше село - частичка России.
В нѐм те же берѐзы, озѐра, луга,
И нет его краше в огромном мире
Ведь это отчизна родная моя.
Здесь я родился, расту и живу,
Здесь всѐ мне родное - родное:
И солнышко в небе, трава на лугу,
И поле во ржи золотое.
3.
4. • А сколько людей рукодельных у нас!
• Хоть в каждый двор заходите:
• В этом - умелец создал тарантас,
• Сбрую расшил и уздечку,
• В этом - плотник себе смастерил
• Диво резное - крылечко.
• Здесь на стене висит чудо - ковѐр,
• А там - пирогом пышет печка,
• В этом - сложили стихи о селе…
• Значит - стоять ему вечно!
•
5.
6. •
• Кружева! Такое откровение,
• Нежности, фантазии полѐт.
• Белоснежной нити завихрение.
• Тот, кто вяжет, тот меня поймѐт.
7. Михайлова Марина
Александровна
• На стекле узоры от мороза,
• А на ткани – от умелых рук.
• Всѐ здесь есть от лепестка да розы
• Крестик, ромбик и волшебный круг!
8. Парыгина Зинаида Степановна
Петельки, крючочки, закорючки.
Как же их в порядок привести?
Умелые и трепетные ручки
Смогут их в узоры заплести!
