Diverse Particle Selection for High-Dimensional Inference in Graphical Models
Department: Computer Science
Quarter: Fall 2017
Seminar Date: Oct 20, 2017
Speaker Name:
Erik Sudderth
Erik Sudderth
Organization:
University of California, Irvine
University of California, Irvine
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Bio:
Erik B. Sudderth is an Associate Professor of Computer Science at the University of California, Irvine. He received the Bachelor's degree (summa cum laude, 1999) in Electrical Engineering from the U…
Erik B. Sudderth is an Associate Professor of Computer Science at the University of California, Irvine. He received the Bachelor's degree (summa cum laude, 1999) in Electrical Engineering from the U…
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Summary:
Rich graphical models for real-world scene understanding encode the shape and pose of objects via high-dimensional, continuous variables. We describe a particle-based max-product inference algorithm…
Rich graphical models for real-world scene understanding encode the shape and pose of objects via high-dimensional, continuous variables. We describe a particle-based max-product inference algorithm…
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Host:
Ardalan Amiri Sani
Ardalan Amiri Sani
Host Notes:
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