Eric Liang

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 29

Top Topics

Reinforcement Learning

Distributed Systems

Top Venues

Proc. VLDB Endow.

Publications

Siyuan Zhuang, Stephanie Wang, Eric Liang, Yi Cheng, Ion Stoica
ExoFlow: A Universal Workflow System for Exactly-Once DAGs. OSDI (2023)
Frank Sifei Luan, Stephanie Wang, Samyukta Yagati, Sean Kim, Kenneth Lien, Isaac Ong, Tony Hong, SangBin Cho, Eric Liang, Ion Stoica
Exoshuffle: An Extensible Shuffle Architecture. SIGCOMM (2023)
Frank Sifei Luan, Stephanie Wang, Samyukta Yagati, Sean Kim, Kenneth Lien, Isaac Ong, Tony Hong, SangBin Cho, Eric Liang, Ion Stoica
Exoshuffle-CloudSort. CoRR (2023)
Eric Liang, Mark Stamp
Predicting Pedestrian Crosswalk Behavior Using Convolutional Neural Networks. CoRR (2022)
Frank Sifei Luan, Stephanie Wang, Samyukta Yagati, Sean Kim, Kenneth Lien, SangBin Cho, Eric Liang, Ion Stoica
Exoshuffle: Large-Scale Shuffle at the Application Level. CoRR (2022)
Stephanie Wang, Eric Liang, Edward Oakes, Benjamin Hindman, Frank Sifei Luan, Audrey Cheng, Ion Stoica
Ownership: A Distributed Futures System for Fine-Grained Tasks. NSDI (2021)
Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Joseph E. Gonzalez, Ion Stoica
RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem. NeurIPS (2021)
Siyuan Zhuang, Zhuohan Li, Danyang Zhuo, Stephanie Wang, Eric Liang, Robert Nishihara, Philipp Moritz, Ion Stoica
Hoplite: efficient and fault-tolerant collective communication for task-based distributed systems. SIGCOMM (2021)
Zongheng Yang, Amog Kamsetty, Sifei Luan, Eric Liang, Yan Duan, Xi Chen, Ion Stoica
NeuroCard: One Cardinality Estimator for All Tables. CoRR (2020)
Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Xi Chen
Variable Skipping for Autoregressive Range Density Estimation. CoRR (2020)
Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Xi Chen
Variable Skipping for Autoregressive Range Density Estimation. ICML (2020)
Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Ion Stoica
Distributed Reinforcement Learning is a Dataflow Problem. CoRR (2020)
Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang, Ion Stoica
IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks. ICLR (2020)
Zongheng Yang, Amog Kamsetty, Sifei Luan, Eric Liang, Yan Duan, Xi Chen, Ion Stoica
NeuroCard: One Cardinality Estimator for All Tables. Proc. VLDB Endow. 14 (1) (2020)
Siyuan Zhuang, Zhuohan Li, Danyang Zhuo, Stephanie Wang, Eric Liang, Robert Nishihara, Philipp Moritz, Ion Stoica
Hoplite: Efficient Collective Communication for Task-Based Distributed Systems. CoRR (2020)
Daniel Ho, Eric Liang, Xi Chen, Ion Stoica, Pieter Abbeel
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. ICML (2019)
Eric Liang, Hang Zhu, Xin Jin, Ion Stoica
Neural Packet Classification. CoRR (2019)
Daniel Ho, Eric Liang, Ion Stoica, Pieter Abbeel, Xi Chen
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. CoRR (2019)
Eric Liang, Hang Zhu, Xin Jin, Ion Stoica
Neural packet classification. SIGCOMM (2019)
Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica
Selectivity Estimation with Deep Likelihood Models. CoRR (2019)
Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang, Ion Stoica
IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks. CoRR (2019)
Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica
Deep Unsupervised Cardinality Estimation. Proc. VLDB Endow. 13 (3) (2019)
Eugene Vinitsky, Aboudy Kreidieh, Luc Le Flem, Nishant Kheterpal, Kathy Jang, Fangyu Wu, Richard Liaw, Eric Liang, Alexandre M. Bayen
Benchmarks for reinforcement learning in mixed-autonomy traffic. CoRL (2018)
Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I. Jordan, Ion Stoica
Ray: A Distributed Framework for Emerging AI Applications. OSDI (2018)
Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Ken Goldberg, Joseph Gonzalez, Michael I. Jordan, Ion Stoica
RLlib: Abstractions for Distributed Reinforcement Learning. ICML (2018)
Richard Liaw, Eric Liang, Robert Nishihara, Philipp Moritz, Joseph E. Gonzalez, Ion Stoica
Tune: A Research Platform for Distributed Model Selection and Training. CoRR (2018)
Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, William Paul, Michael I. Jordan, Ion Stoica
Ray: A Distributed Framework for Emerging AI Applications. CoRR (2017)
Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Joseph Gonzalez, Ken Goldberg, Ion Stoica
Ray RLLib: A Composable and Scalable Reinforcement Learning Library. CoRR (2017)
Shivaram Venkataraman, Zongheng Yang, Davies Liu, Eric Liang, Hossein Falaki, Xiangrui Meng, Reynold Xin, Ali Ghodsi, Michael J. Franklin, Ion Stoica, Matei Zaharia
SparkR: Scaling R Programs with Spark. SIGMOD Conference (2016)
Michael Armbrust, Eric Liang, Tim Kraska, Armando Fox, Michael J. Franklin, David A. Patterson
Generalized scale independence through incremental precomputation. SIGMOD Conference (2013)
Eric Liang, Avideh Zakhor
Structuring a sharded image retrieval database. Multimedia Content and Mobile Devices (2013)
Jerry Zhang, Aaron Hallquist, Eric Liang, Avideh Zakhor
Location-based image retrieval for urban environments. ICIP (2011)
Andrew Y. Ng, Adam Coates, Mark Diel, Varun Ganapathi, Jamie Schulte, Ben Tse, Eric Berger, Eric Liang
Autonomous Inverted Helicopter Flight via Reinforcement Learning. ISER (2004)