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Bookmark or Share- Jonathan HoJonathan Ho. I received my PhD in computer science from UC Berkeley in 2020, advised by Pieter Abbeel. My research interests are unsupervised learning and reinforcement learning. Preprints
- Finding Locally Optimal, Collision-Free Trajectories with Sequential ...John Schulman, Jonathan Ho, Alex Lee, Ibrahim Awwal, Henry Bradlow and Pieter Abbeel Abstract—We present a novel approach for incorporating collision avoidance into trajectory optimization as a method of solving robotic motion planning problems. At the core of our approach are (i) A sequential convex optimization procedure,
- Tracking Deformable Objects with Point CloudsJohn Schulman, Alex Lee, Jonathan Ho, Pieter Abbeel Abstract—We introduce an algorithm for tracking de-formable objects from a sequence of point clouds. The proposed tracking algorithm is based on a probabilistic generative model that incorporates observations of the point cloud and the physical properties of the tracked object and its ...
- Generative Adversarial Imitation LearningJonathan Ho OpenAI hoj@openai.com Stefano Ermon Stanford University ermon@cs.stanford.edu Abstract Consider learning a policy from example expert behavior, without interaction with the expert or access to a reinforcement signal. One approach is to recover the expert’s cost function with inverse reinforcement learning, then extract a policy
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