Miao Liu
Cited by
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Socially Aware Motion Planning with Deep Reinforcement Learning
YF Chen, M Everett, M Liu, JP How
arXiv preprint arXiv:1703.08862, 2017
Learning to learn without forgetting by maximizing transfer and minimizing interference
M Riemer, I Cases, R Ajemian, M Liu, I Rish, Y Tu, G Tesauro
arXiv preprint arXiv:1810.11910, 2018
Decentralized Non-communicating Multiagent Collision Avoidance with Deep Reinforcement Learning
YF Chen, M Liu, M Everett, JP How
arXiv preprint arXiv:1609.07845, 285 - 292, 2016
Eigenoption discovery through the deep successor representation
MC Machado, C Rosenbaum, X Guo, M Liu, G Tesauro, M Campbell
arXiv preprint arXiv:1710.11089, 2017
Learning to teach in cooperative multiagent reinforcement learning
S Omidshafiei, DK Kim, M Liu, G Tesauro, M Riemer, C Amato, ...
Proceedings of the AAAI conference on artificial intelligence 33 (01), 6128-6136, 2019
Gaussian processes for learning and control: A tutorial with examples
M Liu, G Chowdhary, BC Da Silva, SY Liu, JP How
IEEE Control Systems Magazine 38 (5), 53-86, 2018
Learning abstract options
M Riemer, M Liu, G Tesauro
Advances in neural information processing systems 31, 2018
Dynamic clustering via asymptotics of the dependent Dirichlet process mixture
T Campbell, M Liu, B Kulis, JP How, L Carin
Advances in Neural Information Processing Systems 26, 2013
A policy gradient algorithm for learning to learn in multiagent reinforcement learning
DK Kim, M Liu, MD Riemer, C Sun, M Abdulhai, G Habibi, S Lopez-Cot, ...
International Conference on Machine Learning, 5541-5550, 2021
Bi-parameter CGM model for approximation of a-stable PDF
XT Li, J Sun, LW Jin, M Liu
Electronics Letters 44 (18), 1096-1097, 2008
Off-policy reinforcement learning with Gaussian processes
G Chowdhary, M Liu, R Grande, J How
The 1st Multi-disciplinary Conference on Reinforcement Learning and Decision …, 2013
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions
M Liu, K Sivakumar, S Omidshafiei, C Amato, JP How
arXiv preprint arXiv:1707.07399, 2017
Learning hierarchical teaching policies for cooperative agents
DK Kim, M Liu, S Omidshafiei, S Lopez-Cot, M Riemer, G Habibi, ...
arXiv preprint arXiv:1903.03216, 2019
Learning for decentralized control of multiagent systems in large, partially-observable stochastic environments
M Liu, C Amato, E Anesta, J Griffith, J How
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
Stick-breaking policy learning in Dec-POMDPs
M Liu, C Amato, X Liao, L Carin, JP How
International Joint Conference on Artificial Intelligence (IJCAI) 2015, 2015
Augmented Dictionary Learning for Motion Prediction
Y Chen, M Liu, J How
The International Conference on Robotics and Automation, 2527 - 2534, 2016
Motion Planning with Diffusion Maps
Y Chen, S Liu, M Liu, J Miller, J How
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016
A zero-watermarking algorithm based on DWT and chaotic modulation
H Cao, H Xiang, X Li, M Liu, S Yi, F Wei
Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and …, 2006
Mitigating gradient bias in multi-objective learning: A provably convergent approach
H Fernando, H Shen, M Liu, S Chaudhury, K Murugesan, T Chen
International Conference on Learning Representations, 2023
The infinite regionalized policy representation
M Liu, X Liao, L Carin
Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011
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