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:20240310T070000 END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:20231105T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:6830dfc5ec47b DTSTART;TZID=America/Toronto:20240327T103000 SEQUENCE:0 TRANSP:TRANSPARENT DTEND;TZID=America/Toronto:20240327T113000 URL:/computer-science/events/seminar-artificial-intelli gence-mathematical-foundations-for-trustworthy-machine-learning SUMMARY:Seminar • Artificial Intelligence • Mathematical Foundations fo r\nTrustworthy Machine Learning CLASS:PUBLIC DESCRIPTION:Summary \n\nPLEASE NOTE: THIS SEMINAR WILL TAKE PLACE IN DC 130 4.\n\nLUNJIA HU\, PHD CANDIDATE\n_Computer Science Department\, Stanford U niversity_\n\nMachine learning holds significant potential for positive so cietal\nimpact. However\, in critical applications involving people such a s\nhealthcare\, employment\, and lending\, machine learning raises serious \nconcerns of fairness\, robustness\, and interpretability. Addressing\nth ese concerns is crucial for making machine learning more\ntrustworthy.\n DTSTAMP:20250523T205117Z END:VEVENT END:VCALENDAR