| 概要(Abstract)： |
This talk covers simple yet useful matrix algebra that is fundamental to numerical solution methods for various computer vision and signal processing problems. In particular, this talk illustrates some important linear algebraic operations that are crucial for solving optimization problems, together with their applications to computer vision. The talk begins with reviewing basic linear system and norm approximation, then proceeds to methods for deriving sparse and/or low-rank solutions. The talk is designed for people who are not familiar with matrix operations for optimization in computer vision and kept easy to understand.
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