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X-WR-CALDESC:Events for TECoSA
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DTSTART:20220101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20231102T150000
DTEND;TZID=UTC:20231102T160000
DTSTAMP:20260609T062206
CREATED:20230822T092154Z
LAST-MODIFIED:20231023T084022Z
UID:6811-1698937200-1698940800@www.tecosa.center.kth.se
SUMMARY:TECoSA Seminar - Learning Optimal Edge Processing with Offloading and Energy Harvesting
DESCRIPTION:We aim to bring you a TECoSA Seminar on the first Thursday of each month during term-time.  All are welcome to attend and we look forward to some lively discussions. Members can accept the Outlook invitations\, non-members can email tecosa-admin@kth.se to register.\nOur guest speaker for November is Francesco De Pellegrini\, Professor of networking and AI at the University of Avignon\, France.  The seminar will take place via Zoom (https://kth-se.zoom.us/j/66857695267). \nABSTRACT:  Modern portable devices can execute increasingly sophisticated AI models on sensed data. The complexity of such processing tasks is data-dependent and has relevant energy cost. This work develops an Age of Information markovian model for a system where multiple battery-operated devices perform data processing and energy harvesting in parallel. Part of their computational burden is offloaded to an edge server which polls devices at given rate. The structural properties of an optimal policy for a single device-server system are derived. They permit to define a new model-free reinforcement learning method specialized for monotone policies\, namely Ordered Q-Learning\, providing a fast procedure to learn the optimal policy. The method is oblivious to the devices’ battery capacities\, the cost and the value of data batch processing and to the dynamics of the energy harvesting process. Finally\, the polling strategy of the server is optimized by combining this policy improvement technique with stochastic approximation methods. Extensive numerical results provide insight into the system properties and demonstrate that the proposed learning algorithms outperform existing baselines. \nBIO: Francesco De Pellegrini received the MSc 2000\, and the Ph.D. 2004\, in Information Engineering at the University of Padova\, Italy. He is currently full professor at the University of Avignon\, where he teaches networking and artificial intelligence  He has published 100+ papers in major conferences and journals of computer science\, networking and control theory. He applies algorithms on graphs\, stochastic and control\, and game theory for the design and perfomance evaluation of wireless and wired networked systems. He has co-authored two best papers\, published in WiOPT 2014 and at NetGCoop 2016. His current H-index (Google) is 30 with 7000+ citations. He is anassociated editor for TNSE. He has been general co-chair of IEEE NETGCOOP 2012 and IEEE WIOPT2022\, and TPC Co-Chair of IEEE NETGCOOP 2014\, IEEE WIOPT 2018 and ITC 2021.
URL:https://www.tecosa.center.kth.se/event/tecosa-seminar-learning-optimal-edge-processing-with-offloading-and-energy-harvesting/
CATEGORIES:Seminar,Talks,webinar
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BEGIN:VEVENT
DTSTART;TZID=UTC:20231116T130000
DTEND;TZID=UTC:20231116T150000
DTSTAMP:20260609T062206
CREATED:20231027T080926Z
LAST-MODIFIED:20231027T081117Z
UID:6907-1700139600-1700146800@www.tecosa.center.kth.se
SUMMARY:TECoSA Testbeds Demo Session
DESCRIPTION:Due to popular demand\, we will hold a Testbed Demo session for TECoSA members and the IIoT Nordic Network!\nWe open with a welcome to R1\, the historic (and atmospheric) former experimental reactor hall beneath KTH\, followed by a brief overview of the Testbeds and the Demos\, including:\n~ the soft robot\,\n~ the Kvaser car\,\n~ inverted pendulum control\,\n~ and the OpenRtist demos. \nInvitations have been circulated to TECoSA members and special guests.  If you’re interested but not on that list\, please contact Martin Törngren (martint@kth.se).\nTECoSA PhD student Samie Mostafavi\nThe TECoSA Testbeds were inaugurated on 1 September 2023.  You can read more about that here: https://www.tecosa.center.kth.se/2023/09/15/tecosas-new-testbed-environments-show-tomorrows-digital-infrastructures/ \n  \n 
URL:https://www.tecosa.center.kth.se/event/tecosa-testbeds-demo-session/
CATEGORIES:Demo Session
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BEGIN:VEVENT
DTSTART;TZID=UTC:20231121T093000
DTEND;TZID=UTC:20231122T170000
DTSTAMP:20260609T062206
CREATED:20230509T063529Z
LAST-MODIFIED:20230919T080748Z
UID:6465-1700559000-1700672400@www.tecosa.center.kth.se
SUMMARY:SCSSS 2023 – Scandinavian Conference on System & Software Safety
DESCRIPTION:System and software safety in electronic systems is becoming increasingly important in many industries and in critical societal infrastructure. The systems become ever more complex\, connected and autonomous and the software continues to grow. This poses many challenges even for mature organizations\, requiring approaches that go beyond established best practices. Many organizations face the same kind of challenges and thus sharing of experiences becomes essential. \nThis year’s event takes place in Stockholm from 21-22 November. Acknowledged as a central meeting place for Scandinavian safety experts from different industries\, the SCSSS is an opportunity to share experiences and make new contacts. There will be an overview day followed by a day of parallel sessions with in depth presentations and discussions about different challenges\, techniques\, standards and methods. This year’s keynotes are Nancy Leveson (MIT)\, Ibrahim Habli (University of York) and Lena Kecklund (MTO Säkerhet AB). \n\n\nSee the conference homepage for more details: http://safety.addalot.se/20223
URL:https://www.tecosa.center.kth.se/event/scsss-2023-scandinavian-conference-on-system-software-safety/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20231124T120000
DTEND;TZID=UTC:20231124T130000
DTSTAMP:20260609T062206
CREATED:20231109T131229Z
LAST-MODIFIED:20231109T131229Z
UID:6965-1700827200-1700830800@www.tecosa.center.kth.se
SUMMARY:TECoSA Research Seminar: Learn and Align RL Policies from Human Feedback
DESCRIPTION:Speaker: Daniel Simões Marta\, TECoSA PhD student\n(Venue\, Zoom link and sign-up link circulated to members)\nPlease email vickid@kth.se if you have any questions. \nABSTRACT: Reinforcement learning from informed by human feedback (RLHF) has emerged as a novel domain in machine learning\, where human insights are crucial in shaping the behavior of an AI agent. Within this domain\, a significant strategy is preference-based reinforcement learning\, in which a human-informed reward system is developed through the evaluation and selection among different sets of action sequences. In this talk\, I will present several works conducted by our group on aligning RL policies with human feedback. I will primarily focus on aligning relevant features such as safety and perceived safety—even though the work can be extended to any desired feature—and will discuss the application of these principles in the context of RL policies. Additionally\, I will provide concrete examples of leveraging human intrinsic knowledge through methods such as ranking\, stating preferences\, and analyzing text.
URL:https://www.tecosa.center.kth.se/event/tecosa-research-seminar-learn-and-align-rl-policies-from-human-feedback/
CATEGORIES:Seminar,Talks,webinar
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