BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.16.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251110T130000
DTEND;TZID=America/New_York:20251110T140000
DTSTAMP:20260601T201850
CREATED:20251104T141359Z
LAST-MODIFIED:20251104T141359Z
UID:15083-1762779600-1762783200@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Seminar: "Temporal Knockoffs: Variable selection for time-varying systems with e-processes"
DESCRIPTION:One of the primary goals of ‘explainable AI’ is the identification of a small subset of explanatory variables in an attempt to understand interesting phenomena. The Markov blanket constitutes one such subset\, essential for tasks involving causal interpretation\, prediction\, and robustness. In medical imaging\, identifying such variables is particularly important for achieving generalization across sites and mitigating domain shifts induced by scanner or population biases. Existing approaches based on the model-X knockoffs framework (Barber & Candès\, 2015) provide finite-sample control of the false discovery rate (FDR) under the IID assumption. However\, longitudinal data violate this assumption and exhibit temporal dependencies\, non-stationarity\, making the standard knockoff constructions invalid. In this work\, we explore a principled extension of knockoff-based variable selection to time-varying systems by leveraging ideas from betting games and e-processes in sequential hypothesis testing. We explore its applicability to both synthetic datasets as well as test it on real-world longitudinal neuro-imaging data from ADNI.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-seminar/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
END:VCALENDAR