17:30 〜 18:10
[2Q6-OS-20b-01] (OS invited talk) Principle-centric AI for Embodied Intelligence
キーワード：Deep learning, Computer vision
How can we get Deep Learning's success on the web to translate to intelligent machines physically interacting with the real-world, especially for safety-critical systems like cars and robots? In this talk, I will describe our unique approach to the problem of embodied intelligence: Principle-centric AI. It consists in going beyond mere data, the main workhorse of DL, by complementing it with guiding principles to increase safety, sample efficiency, and robustness. I will showcase a few examples of cutting edge computer vision research showing how to leverage geometric principles as self-supervised objectives and inductive priors to not just let machines learn by examples, but actually guide them as teachers towards better outcomes.
講演PDFパスワード認証
論文PDFの閲覧にはログインが必要です。参加登録者の方は「参加者用ログイン」画面からログインしてください。あるいは論文PDF閲覧用のパスワードを以下にご入力ください。