Eric Liang | DeepAI

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∙ 01/10/2023

Exoshuffle-CloudSort

We present Exoshuffle-CloudSort, a sorting application running on top of...

0 Frank Sifei Luan, et al. ∙

∙ 08/08/2022

Predicting Pedestrian Crosswalk Behavior Using Convolutional Neural Networks

A common yet potentially dangerous task is the act of crossing the stree...

13 Eric Liang, et al. ∙

∙ 03/09/2022

Exoshuffle: Large-Scale Shuffle at the Application Level

Shuffle is a key primitive in large-scale data processing applications. ...

0 Frank Sifei Luan, et al. ∙

∙ 11/25/2020

Distributed Reinforcement Learning is a Dataflow Problem

Researchers and practitioners in the field of reinforcement learning (RL...

20 Eric Liang, et al. ∙

∙ 07/10/2020

Variable Skipping for Autoregressive Range Density Estimation

Deep autoregressive models compute point likelihood estimates of individ...

2 Eric Liang, et al. ∙

∙ 06/15/2020

NeuroCard: One Cardinality Estimator for All Tables

Query optimizers rely on accurate cardinality estimates to produce good ...

0 Zongheng Yang, et al. ∙

∙ 02/13/2020

Hoplite: Efficient Collective Communication for Task-Based Distributed Systems

Collective communication systems such as MPI offer high performance grou...

0 Siyuan Zhuang, et al. ∙

∙ 11/30/2019

IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks

The practical usage of reinforcement learning agents is often bottleneck...

5 Michael Luo, et al. ∙

∙ 05/14/2019

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules

A key challenge in leveraging data augmentation for neural network train...

2 Daniel Ho, et al. ∙

∙ 05/10/2019

Selectivity Estimation with Deep Likelihood Models

Selectivity estimation has long been grounded in statistical tools for d...

0 Zongheng Yang, et al. ∙

∙ 02/27/2019

Neural Packet Classification

Packet classification is a fundamental problem in computer networking. T...

0 Eric Liang, et al. ∙

∙ 07/13/2018

Tune: A Research Platform for Distributed Model Selection and Training

Modern machine learning algorithms are increasingly computationally dema...

0 Richard Liaw, et al. ∙

∙ 12/26/2017

Ray RLLib: A Composable and Scalable Reinforcement Learning Library

Reinforcement learning (RL) algorithms involve the deep nesting of disti...

1 Eric Liang, et al. ∙

∙ 12/16/2017

Ray: A Distributed Framework for Emerging AI Applications

The next generation of AI applications will continuously interact with t...

0 Philipp Moritz, et al. ∙

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