- survey several important computational problems for which the traditional worst-case analysis of algorithms is ill-suited
- study systematically alternatives to worst-case analysis
Learn AI from Stanford professors Christopher Manning, Andrew Ng, and Emma Brunskill. Free online course videos in Deep Learning, Reinforcement Learning, and Natural Language Processing.
It is a research group under the Stanford Vision & Learning Lab that focuses on developing methods and mechanisms for generalizable robot perception and control.
We work on challenging open problems at the intersection of computer vision, machine learning, and robotics. We develop algorithms and systems that unify in reinforcement learning, control theoretic modeling, and 2D/3D visual scene understanding to teach robots to perceive and to interact with the physical world.