BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Amsterdam BEGIN:DAYLIGHT DTSTART:20220327T030000 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20221030T020000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20221204T212314Z UID:0AFFF568-0161-430D-8D2E-97417D3D2C89 DTSTART;TZID=Europe/Amsterdam:20220629T160000 DTEND;TZID=Europe/Amsterdam:20220629T172000 DESCRIPTION:Your local chapters of AESS\, SPS\, and OES are joining togethe r to enhance your local San Diego technical community.\n\nPrivacy issues a nd communication costs are both major concerns in distributed optimization in networks. There is often a tradeoff between them because encryption me thods used for privacy-preservation often introduce significant communicat ion overhead. In this talk\, we discuss a quantization-based approach to a chieve both communication efficiency and privacy-preserving in the context of distributed optimization. By deploying an adaptive differential quanti zation scheme\, we allow each node in the network to achieve the optimum s olution with low communication costs while keeping its private data unreve aled. The proposed approach is general and can be applied in various distr ibuted optimization methods\, such as dual ascent and methods based on ope rator splitting (PDMM and ADMM). We consider two widely used adversary mod els\, passive and eavesdropping\, and investigate the properties of the pr oposed approach using different applications and demonstrate its superior performance compared to existing privacy-preserving approaches in terms of privacy\, accuracy\, and communication cost.\n\nThis virtual event has be en organized by the [IEEE Signal Processing Society Information and Forens ics Security Technical Committee (SPS-IFS-TC)](https://signalprocessingsoc iety.us4.list-manage.com/track/click?u=25f275b5af555643e88abfbcb&id=be4ffc 516b&e=5ec69d6def) and fits well with the technical interests of the IEEE Aerospace & Electronics Systems Society Cyber Technical Panel.\n\nYou can view virtual events in this series at https://signalprocessingsociety.org/ tags/sps-webinar-series.\n\nPlease note that this meeting starts at 7AM pa cific time\, as it's coming from The Netherlands.\n\nSpeaker(s): Richard H eusdens\, \n\nVirtual: https://events.vtools.ieee.org/m/317081 LOCATION:Virtual: https://events.vtools.ieee.org/m/317081 ORGANIZER:k.kramer@ieee.org SEQUENCE:5 SUMMARY:Virtual Distinguished Lecture - Communication Efficient Privacy-Pre serving Distributed Optimization URL;VALUE=URI:https://events.vtools.ieee.org/m/317081 X-ALT-DESC:Description: <br /><p>Your local chapters of AESS\, SPS\, and OE S are joining together to enhance your local San Diego technical community .</p>\n<p>Privacy issues and communication costs are both major concerns i n distributed optimization in networks. There is often a tradeoff between them because encryption methods used for privacy-preservation often introd uce significant communication overhead. In this talk\, we discuss a quanti zation-based approach to achieve both communication efficiency and privacy -preserving in the context of distributed optimization. By deploying an ad aptive differential quantization scheme\, we allow each node in the networ k to achieve the optimum solution with low communication costs while keepi ng its private data unrevealed. The proposed approach is general and can b e applied in various distributed optimization methods\, such as dual ascen t and methods based on operator splitting (PDMM and ADMM). We consider two widely used adversary models\, passive and eavesdropping\, and investigat e the properties of the proposed approach using different applications and demonstrate its superior performance compared to existing privacy-preserv ing approaches in terms of privacy\, accuracy\, and communication cost.</p >\n<p>This virtual event has been organized by the <a title="https://signa lprocessingsociety.us4.list-manage.com/track/click?u=25f275b5af555643e88ab fbcb&amp\;id=be4ffc516b&amp\;e=5ec69d6def" contenteditable="false" href="h ttps://signalprocessingsociety.us4.list-manage.com/track/click?u=25f275b5a f555643e88abfbcb&amp\;id=be4ffc516b&amp\;e=5ec69d6def" target="_blank" rel ="noopener">IEEE Signal Processing Society Information and Forensics Secur ity Technical Committee (SPS-IFS-TC)</a> and fits well with the technical interests of the IEEE Aerospace &amp\; Electronics Systems Society Cyber T echnical Panel.</p>\n<p>You can view virtual events in this series at http s://signalprocessingsociety.org/tags/sps-webinar-series.</p>\n<p>Please no te that this meeting starts at 7AM pacific time\, as it's coming from The Netherlands.</p> END:VEVENT END:VCALENDAR