Data-Efficient Scalable Reinforcement Learning for Practical Robotic Environments

Pubblicazioni

Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Online Hybrid Model Predictive Control

Autori: Jia-Jie Zhu, Georg Martius
Pubblicato in: 2020
Editore: Elsevier

Control What You Can: Intrinsically Motivated Task-Planning Agent

Autori: Sebastian Blaes, Marin Vlastelica Pogančić, JJ Zhu, Georg Martius
Pubblicato in: 2019
Editore: Neural Information Processing Systems Foundation, Inc.

Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning

Autori: Mohammad Hasan Yeganegi, Majid Khadiv, S Ali A Moosavian, Jia-Jie Zhu, Andrea Del Prete, Ludovic Righetti
Pubblicato in: 2020
Editore: IEEE

A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming

Autori: Jia-Jie Zhu, Krikamol Muandet, Moritz Diehl, Bernhard Schölkopf
Pubblicato in: 2020
Editore: Elsevier

A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control

Autori: Jia-Jie Zhu, Moritz Diehl, Bernhard Schölkopf
Pubblicato in: 2020
Editore: Proceedings of Machine Learning Research

Deep Reinforcement Learning for Event-Triggered Control

Autori: Baumann, Dominik; Zhu, Jia-Jie; Martius, Georg; Trimpe, Sebastian
Pubblicato in: 2018
Editore: IEEE

Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem

Autori: Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
Pubblicato in: 2020
Editore: Under review

Kernel Distributionally Robust Optimization

Autori: Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
Pubblicato in: 2020
Editore: Under review

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