BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:PNA T32 Training Grant Seminar: A mini course on probabilistic
  machine learning for large data analysis
X-WR-TIMEZONE:Eastern Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260813T061936Z
UID:tag:localist.com\,2008:EventInstance_49640747660942
DTSTART:20250514T150000Z
DTEND:20250514T160000Z
DESCRIPTION:Led by Faculty Member Seyoung Kim and Doctoral Student Richard 
 Xu. \n\nMay 14\nTopic: How can we represent relationships among many inter
 related features? \nFocus: Bayesian network I: model\n\nJune 4\nTopic: How
  can we learn relationships among many interrelated features? \nFocus: Bay
 esian network II: learning and interference\n\nJuly 23\nTopic: Workshop on
  omics data analysis \nFocus: Hierarchichal clustering\, pathway enrichmen
 t analysis\n\nAugust 6 \nTopic: How can we find groups of correlated featu
 res? \nFocus: Mixture models as a special case of Bayesian networks
LOCATION:
SUMMARY:PNA T32 Training Grant Seminar: A mini course on probabilistic mach
 ine learning for large data analysis
URL;VALUE=URI:https://calendar.pitt.edu/event/pna-t32-training-grant-semina
 r-a-mini-course-on-probabilistic-machine-learning-for-large-data-analysis
CATEGORIES:Lectures\, Symposia\, Etc.
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260813T061936Z
UID:tag:localist.com\,2008:EventInstance_49640720457580
DTSTART:20250604T150000Z
DTEND:20250604T160000Z
DESCRIPTION:Led by Faculty Member Seyoung Kim and Doctoral Student Richard 
 Xu. \n\nMay 14\nTopic: How can we represent relationships among many inter
 related features? \nFocus: Bayesian network I: model\n\nJune 4\nTopic: How
  can we learn relationships among many interrelated features? \nFocus: Bay
 esian network II: learning and interference\n\nJuly 23\nTopic: Workshop on
  omics data analysis \nFocus: Hierarchichal clustering\, pathway enrichmen
 t analysis\n\nAugust 6 \nTopic: How can we find groups of correlated featu
 res? \nFocus: Mixture models as a special case of Bayesian networks
LOCATION:
SUMMARY:PNA T32 Training Grant Seminar: A mini course on probabilistic mach
 ine learning for large data analysis
URL;VALUE=URI:https://calendar.pitt.edu/event/pna-t32-training-grant-semina
 r-a-mini-course-on-probabilistic-machine-learning-for-large-data-analysis
CATEGORIES:Lectures\, Symposia\, Etc.
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260813T061936Z
UID:tag:localist.com\,2008:EventInstance_49640720459629
DTSTART:20250723T150000Z
DTEND:20250723T160000Z
DESCRIPTION:Led by Faculty Member Seyoung Kim and Doctoral Student Richard 
 Xu. \n\nMay 14\nTopic: How can we represent relationships among many inter
 related features? \nFocus: Bayesian network I: model\n\nJune 4\nTopic: How
  can we learn relationships among many interrelated features? \nFocus: Bay
 esian network II: learning and interference\n\nJuly 23\nTopic: Workshop on
  omics data analysis \nFocus: Hierarchichal clustering\, pathway enrichmen
 t analysis\n\nAugust 6 \nTopic: How can we find groups of correlated featu
 res? \nFocus: Mixture models as a special case of Bayesian networks
LOCATION:
SUMMARY:PNA T32 Training Grant Seminar: A mini course on probabilistic mach
 ine learning for large data analysis
URL;VALUE=URI:https://calendar.pitt.edu/event/pna-t32-training-grant-semina
 r-a-mini-course-on-probabilistic-machine-learning-for-large-data-analysis
CATEGORIES:Lectures\, Symposia\, Etc.
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260813T061936Z
UID:tag:localist.com\,2008:EventInstance_49640720461678
DTSTART:20250806T150000Z
DTEND:20250806T160000Z
DESCRIPTION:Led by Faculty Member Seyoung Kim and Doctoral Student Richard 
 Xu. \n\nMay 14\nTopic: How can we represent relationships among many inter
 related features? \nFocus: Bayesian network I: model\n\nJune 4\nTopic: How
  can we learn relationships among many interrelated features? \nFocus: Bay
 esian network II: learning and interference\n\nJuly 23\nTopic: Workshop on
  omics data analysis \nFocus: Hierarchichal clustering\, pathway enrichmen
 t analysis\n\nAugust 6 \nTopic: How can we find groups of correlated featu
 res? \nFocus: Mixture models as a special case of Bayesian networks
LOCATION:
SUMMARY:PNA T32 Training Grant Seminar: A mini course on probabilistic mach
 ine learning for large data analysis
URL;VALUE=URI:https://calendar.pitt.edu/event/pna-t32-training-grant-semina
 r-a-mini-course-on-probabilistic-machine-learning-for-large-data-analysis
CATEGORIES:Lectures\, Symposia\, Etc.
END:VEVENT
END:VCALENDAR