On the Convergence Rate of Decomposable Submodular Function Minimization. - Robert Nishihara; Stefanie Jegelka; Michael I. Jordan (NIPS, 2014)

Parallel MCMC with generalized elliptical slice sampling. - Robert Nishihara; Iain Murray 001; Ryan P. Adams (J. Mach. Learn. Res., 2014)

A General Analysis of the Convergence of ADMM. - Robert Nishihara; Laurent Lessard; Benjamin Recht; Andrew K. Packard; Michael I. Jordan (ICML, 2015)

A Linearly-Convergent Stochastic L-BFGS Algorithm. - Philipp Moritz; Robert Nishihara; Michael I. Jordan (AISTATS, 2016)

No Regret Bound for Extreme Bandits. - Robert Nishihara; David Lopez-Paz; Léon Bottou (AISTATS, 2016)

SparkNet: Training Deep Networks in Spark. - Philipp Moritz; Robert Nishihara; Ion Stoica; Michael I. Jordan (ICLR (Poster), 2016)

Discovering Causal Signals in Images. - David Lopez-Paz; Robert Nishihara; Soumith Chintala; Bernhard Schölkopf; Léon Bottou (CVPR, 2017)

Real-Time Machine Learning: The Missing Pieces. - Robert Nishihara; Philipp Moritz; Stephanie Wang; Alexey Tumanov; William Paul; Johann Schleier-Smith; Richard Liaw; Mehrdad Niknami; Michael I. Jordan; Ion Stoica (HotOS, 2017)

Ray: A Distributed Framework for Emerging AI Applications. - Philipp Moritz; Robert Nishihara; Stephanie Wang; Alexey Tumanov; Richard Liaw; Eric Liang; William Paul; Michael I. Jordan; Ion Stoica (CoRR, 2017)

Ray RLLib: A Composable and Scalable Reinforcement Learning Library. - Eric Liang; Richard Liaw; Robert Nishihara; Philipp Moritz; Roy Fox; Joseph Gonzalez 001; Ken Goldberg; Ion Stoica (CoRR, 2017)

RLlib: Abstractions for Distributed Reinforcement Learning. - Eric Liang; Richard Liaw; Robert Nishihara; Philipp Moritz; Roy Fox; Ken Goldberg; Joseph Gonzalez 001; Michael I. Jordan; Ion Stoica (ICML, 2018)

Ray: A Distributed Framework for Emerging AI Applications. - Philipp Moritz; Robert Nishihara; Stephanie Wang; Alexey Tumanov; Richard Liaw; Eric Liang; Melih Elibol; Zongheng Yang; William Paul; Michael I. Jordan; Ion Stoica (OSDI, 2018)

Tune: A Research Platform for Distributed Model Selection and Training. - Richard Liaw; Eric Liang; Robert Nishihara; Philipp Moritz; Joseph E. Gonzalez; Ion Stoica (CoRR, 2018)

Lineage stash: fault tolerance off the critical path. - Stephanie Wang; John Liagouris; Robert Nishihara; Philipp Moritz; Ujval Misra; Alexey Tumanov; Ion Stoica (SOSP, 2019)

Policy Gradient Search: Online Planning and Expert Iteration without Search Trees. - Thomas Anthony 001; Robert Nishihara; Philipp Moritz; Tim Salimans; John Schulman (CoRR, 2019)

On Systems and Algorithms for Distributed Machine Learning. - Robert Nishihara (2019)

Hoplite: Efficient Collective Communication for Task-Based Distributed Systems. - Siyuan Zhuang; Zhuohan Li 001; Danyang Zhuo; Stephanie Wang; Eric Liang; Robert Nishihara; Philipp Moritz; Ion Stoica (CoRR, 2020)

Hoplite: efficient and fault-tolerant collective communication for task-based distributed systems. - Siyuan Zhuang; Zhuohan Li 001; Danyang Zhuo; Stephanie Wang; Eric Liang; Robert Nishihara; Philipp Moritz; Ion Stoica (SIGCOMM, 2021)

ESCHER: expressive scheduling with ephemeral resources. - Romil Bhardwaj; Alexey Tumanov; Stephanie Wang; Richard Liaw; Philipp Moritz; Robert Nishihara; Ion Stoica (SoCC, 2022)