Michael Luo

According to our database, Michael Luo authored at least 16 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

SimpleStrat: Diversifying Language Model Generation with Stratification.

Justin Wong, Yury Orlovskiy, Michael Luo, Sanjit A. Seshia, Joseph E. Gonzalez

CoRR, 2024

Stylus: Automatic Adapter Selection for Diffusion Models.

Michael Luo, Justin Wong, Brandon Trabucco, Yanping Huang, Joseph E. Gonzalez, Zhifeng Chen, Ruslan Salakhutdinov, Ion Stoica

CoRR, 2024

Starburst: A Cost-aware Scheduler for Hybrid Cloud.

Michael Luo, Siyuan Zhuang, Suryaprakash Vengadesan, Romil Bhardwaj, Justin Chang, Eric J. Friedman, Scott Shenker, Ion Stoica

Proceedings of the 2024 USENIX Annual Technical Conference, 2024

2023

SkyPilot: An Intercloud Broker for Sky Computing.

Zongheng Yang, Zhanghao Wu, Michael Luo, Wei-Lin Chiang, Romil Bhardwaj, Woosuk Kwon, Siyuan Zhuang, Frank Sifei Luan, Gautam Mittal, Scott Shenker, Ion Stoica

Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, 2023

2022

Balsa: Learning a Query Optimizer Without Expert Demonstrations.

Zongheng Yang, Wei-Lin Chiang, Sifei Luan, Gautam Mittal, Michael Luo, Ion Stoica

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021

Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones.

Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg

IEEE Robotics Autom. Lett., 2021

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance.

Michael Luo, Ashwin Balakrishna, Brijen Thananjeyan, Suraj Nair, Julian Ibarz, Jie Tan, Chelsea Finn, Ion Stoica, Ken Goldberg

CoRR, 2021

RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem.

Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Joseph E. Gonzalez, Ion Stoica

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Accelerating Quadratic Optimization with Reinforcement Learning.

Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Seed Placements and Automation Policies for Polyculture Farming with Companion Plants.

Yahav Avigal, Anna Deza, William Wong, Sebastian Oehme, Mark Presten, Mark Theis, Jackson Chui, Paul Shao, Huang Huang, Atsunobu Kotani, Satvik Sharma, Rishi Parikh, Michael Luo, Sandeep Mukherjee, Stefano Carpin, Joshua H. Viers, Stavros Vougioukas, Ken Goldberg

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Discovering Non-monotonic Autoregressive Orderings with Variational Inference.

Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen, Trevor Darrell, Yang Gao

Proceedings of the 9th International Conference on Learning Representations, 2021

LazyDAgger: Reducing Context Switching in Interactive Imitation Learning.

Ryan Hoque, Ashwin Balakrishna, Carl Putterman, Michael Luo, Daniel S. Brown, Daniel Seita, Brijen Thananjeyan, Ellen R. Novoseller, Ken Goldberg

Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

2020

Context-Conditioning as Cognitive Control: Guiding Meta-learning with Task Information.

Rachit Dubey, Erin Grant, Michael Luo, Karthik Narasimhan, Thomas L. Griffiths

CoRR, 2020

Distributed Reinforcement Learning is a Dataflow Problem.

Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Ion Stoica

CoRR, 2020

IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks.

Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang, Ion Stoica

Proceedings of the 8th International Conference on Learning Representations, 2020

2014

Clinical, functional, and radiographic outcomes following total knee arthroplasty with patient-specific instrumentation, computer-assisted surgery, and manual instrumentation: a short-term follow-up study.

Mark Yaffe, Michael Luo, Nitin Goyal, Philip Chan, Anay Patel, Max Cayo, S. David Stulberg

Int. J. Comput. Assist. Radiol. Surg., 2014