703644 Probabilistic Models and Inference

summer semester 2013 | Last update: 16.07.2013 Place course on memo list
Department of Computer Science Department of Computer Science
Univ.-Prof. Justus Piater, PhD Univ.-Prof. Justus Piater, PhD, +43 512 507 53264
703644
Probabilistic Models and Inference
VO 1
2
weekly
annually
English
Probabilistic models and machine learning play key roles in diverse applications. This course presents some such applications taken from computer vision, robotics, and/or artificial intelligence, and discusses their underlying, proven, versatile methods of probabilistic modeling and machine learning. Students who successfully complete this course are capable of understanding and applying these and similar methods.
Possible example applications are object tracking in video, structured, probabilistic object recognition, simultaneous localization and mapping (SLAM), recommender systems, robot motor learning, natural language processing. Example methods are the Kalman filter, particle filters, partially observable Markov decision processes (POMDP), hidden Markov models (HMM), policy-search reinforcement learning, inverse reinforcement learning.
Motivated by practical applications, the lecture covers theoretical material that the complementary proseminar exercises in discussions, written problems, and programming projects.
Oral Exam
See Link.
The course is designed as VO+PS. All participants are expected to participate in both VO and PS. Some material builds on concepts taught in the Advanced Machine Learning (703642) course.
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Date Time Location
Mon 2013-03-04
 11.15 - 12.00 HS 10 HS 10 Barrier-free
Mon 2013-03-11
 11.15 - 12.00 HS 10 HS 10 Barrier-free
Mon 2013-03-18
 11.15 - 12.00 HS 10 HS 10 Barrier-free
Mon 2013-04-08
 11.15 - 12.00 HS 10 HS 10 Barrier-free
Mon 2013-04-15
 11.15 - 12.00 HS 10 HS 10 Barrier-free
Mon 2013-04-22
 11.15 - 12.00 HS 10 HS 10 Barrier-free
Mon 2013-04-29
 11.15 - 12.00 SR Container 1 SR Container 1
Mon 2013-05-06
 11.15 - 12.00 HS 10 HS 10 Barrier-free
Mon 2013-05-27
 11.15 - 12.00 SR Container 1 SR Container 1
Mon 2013-06-03
 11.15 - 12.00 SR Container 1 SR Container 1
Mon 2013-06-10
 11.15 - 12.00 SR Container 1 SR Container 1
Mon 2013-06-17
 11.15 - 12.00 SR Container 1 SR Container 1
Mon 2013-06-24
 11.15 - 12.00 SR Container 1 SR Container 1