BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Madrid BEGIN:DAYLIGHT DTSTART:20240331T030000 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20241027T020000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240528T084129Z UID:DECC768F-EC4B-4E34-AFE6-EEC77B8B897F DTSTART;TZID=Europe/Madrid:20240506T131500 DTEND;TZID=Europe/Madrid:20240506T141500 DESCRIPTION:On Monday\, May 6\, Prof. Chao Tian from Texas A&M University w ill visit the Universidad Carlos III de Madrid\, Campus Leganés\, to give his Distinguished Lecture:\n\nTitle: "Computer-Aided Investigation of Inf ormation-Theoretic Limits: An Overview”\n\nAbstract: The linear programm ing (LP) formulation of information measures provides a solid mathematical framework to identify the fundamental limits of information systems compu tationally. A critical issue of this approach is however its high computat ional complexity. To reduce the computation burden of this approach\, we c an utilize the symmetry structure in such systems. The strength of the sym metry-reduced approach is illustrated in several well-known difficult prob lems\, such as regenerating codes\, coded caching\, and private informatio n retrieval\, which provides new and non-trivial outer bounds. In addition to rate bounds\, more in-depth studies can be conducted on the joint entr opy structure of these computed bounds\, which often lead to reverse-engin eered novel code constructions and further allow disproving linear code ac hievability. Finally\, we discuss two new directions: the first is to allo w the utilization of non-Shannon-type inequalities in the computational ap proach\, and the second is to convert the original LP into a sequence of s maller LPs\, both of which appear to be awaiting certain suitable machine- learning techniques.\n\nSpeaker(s): Dr. Chao Tian\n\nRoom: 4.1.D01\, Bldg: Torres Quevedo\, Universidad Carlos III de Madrid\, Leganés\, Av. de la Universidad 30\, Leganés\, Madrid\, Spain\, 28911 LOCATION:Room: 4.1.D01\, Bldg: Torres Quevedo\, Universidad Carlos III de M adrid\, Leganés\, Av. de la Universidad 30\, Leganés\, Madrid\, Spain\, 28911 ORGANIZER:grace.villacres@urjc.es SEQUENCE:55 SUMMARY:IEEE Distinguished Lecture by Chao Tian (Texas A&M University) URL;VALUE=URI:https://events.vtools.ieee.org/m/416900 X-ALT-DESC:Description: <br /><p class="MsoNormal"><span lang="EN-GB" style ="mso-ansi-language: EN-GB\;">On Monday\, May 6\, Prof. Chao Tian from Tex as A&amp\;M University will visit the Universidad Carlos III de Madrid\, C ampus Legan&eacute\;s\, to give his Distinguished Lecture:&nbsp\;</span></ p>\n<p class="MsoNormal"><span lang="EN-GB" style="mso-ansi-language: EN-G B\;"><strong>Title: "<span style="color: rgb(0\, 0\, 0)\;">Computer-Aided Investigation of Information-Theoretic Limits: An Overview</span>&rdquo\;< /strong></span></p>\n<p class="MsoNormal"><span lang="EN-GB" style="mso-an si-language: EN-GB\;"><strong>Abstract: </strong>The linear programming (L P) formulation of information measures provides a solid mathematical frame work to identify the fundamental limits of information systems computation ally. A critical issue of this approach is however its high computational complexity. To reduce the computation burden of this approach\, we can uti lize the symmetry structure in such systems. The strength of the symmetry- reduced approach is illustrated in several well-known difficult problems\, such as regenerating codes\, coded caching\, and private information retr ieval\, which provides new and non-trivial outer bounds. In addition to ra te bounds\, more in-depth studies can be conducted on the joint entropy st ructure of these computed bounds\, which often lead to reverse-engineered novel code constructions and further allow disproving linear code achievab ility. Finally\, we discuss two new directions: the first is to allow the utilization of non-Shannon-type inequalities in the computational approach \, and the second is to convert the original LP into a sequence of smaller LPs\, both of which appear to be awaiting certain suitable machine-learni ng techniques.</span></p>\n<p class="MsoNormal">&nbsp\;</p> END:VEVENT END:VCALENDAR