BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Drupal iCal API//EN X-WR-CALNAME:Events items teaser X-WR-TIMEZONE:America/Toronto BEGIN:VTIMEZONE TZID:America/Toronto X-LIC-LOCATION:America/Toronto BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:20230312T070000 END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:20221106T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:6830eb5a112fa DTSTART;TZID=America/Toronto:20230420T130000 SEQUENCE:0 TRANSP:TRANSPARENT DTEND;TZID=America/Toronto:20230420T140000 URL:/computer-science/events/seminar-machine-learning-b ackpropagation-beyond-gradient SUMMARY:Seminar • Machine Learning • Backpropagation Beyond the Gradien t CLASS:PUBLIC DESCRIPTION:Summary \n\nPLEASE NOTE: THIS SEMINAR WILL TAKE PLACE IN DC 258 5.\n\nFELIX DANGEL\, POSTDOCTORAL RESEARCHER\n_Vector Institute for Artifi cial Intelligence_\n\nPopular deep learning frameworks prioritize computin g the average\nmini-batch gradient. Yet\, other quantities such as its var iance or\nmany approximations to the Hessian can be computed efficiently\, and at\nthe same time as the gradient mean. They are of great interest to \nresearchers and practitioners\, but implementing them is often\nburdenso me or inefficient.\n DTSTAMP:20250523T214042Z END:VEVENT END:VCALENDAR