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01/10/2023
Exoshuffle-CloudSort
We present Exoshuffle-CloudSort, a sorting application running on top of...
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08/08/2022
Predicting Pedestrian Crosswalk Behavior Using Convolutional Neural Networks
A common yet potentially dangerous task is the act of crossing the stree...
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03/09/2022
Exoshuffle: Large-Scale Shuffle at the Application Level
Shuffle is a key primitive in large-scale data processing applications. ...
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11/25/2020
Distributed Reinforcement Learning is a Dataflow Problem
Researchers and practitioners in the field of reinforcement learning (RL...
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07/10/2020
Variable Skipping for Autoregressive Range Density Estimation
Deep autoregressive models compute point likelihood estimates of individ...
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06/15/2020
NeuroCard: One Cardinality Estimator for All Tables
Query optimizers rely on accurate cardinality estimates to produce good ...
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02/13/2020
Hoplite: Efficient Collective Communication for Task-Based Distributed Systems
Collective communication systems such as MPI offer high performance grou...
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11/30/2019
IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks
The practical usage of reinforcement learning agents is often bottleneck...
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05/14/2019
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
A key challenge in leveraging data augmentation for neural network train...
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05/10/2019
Selectivity Estimation with Deep Likelihood Models
Selectivity estimation has long been grounded in statistical tools for d...
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02/27/2019
Neural Packet Classification
Packet classification is a fundamental problem in computer networking. T...
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07/13/2018
Tune: A Research Platform for Distributed Model Selection and Training
Modern machine learning algorithms are increasingly computationally dema...
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12/26/2017
Ray RLLib: A Composable and Scalable Reinforcement Learning Library
Reinforcement learning (RL) algorithms involve the deep nesting of disti...
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12/16/2017