180 citations
- Massachusetts Institute of TechnologyUS38 papers
- University of BonnDE37 papers
- University of OxfordGB36 papers
- Centre National de la Recherche ScientifiqueFR35 papers
- Centro Brasileiro de Pesquisas FísicasBR35 papers
- École Polytechnique Fédérale de LausanneCH35 papers
- Lamarr Institute for Machine Learning and Artificial Intelligence35 papers
- Ruhr University BochumDE35 papers
- Sorbonne UniversitéFR35 papers
- University of BolognaIT35 papers
- University of CambridgeGB35 papers
- University of SienaIT35 papers
Showing 2018 · cs.LGShow all
2 papers · 2 filters
cs.LG2018★ 84 cited
Improving the Generalization of Adversarial Training with Domain Adaptation
Chuanbiao Song, Kun He, Liwei Wang +1
By injecting adversarial examples into training data, adversarial training is promising for improving the robustness of deep learning models. However, most existing adversarial tra…
cs.LG2018★ 180 cited
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
Kurtland Chua, Roberto Calandra, Rowan McAllister +1
Model-based reinforcement learning (RL) algorithms can attain excellent sample efficiency, but often lag behind the best model-free algorithms in terms of asymptotic performance. T…