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07/10/2023
Measuring and Mitigating Interference in Reinforcement Learning
Catastrophic interference is common in many network-based learning syste...
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02/23/2023
Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments
In this work, we consider the off-policy policy evaluation problem for c...
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07/26/2022
FP4: Line-rate Greybox Fuzz Testing for P4 Switches
Compared to fixed-function switches, the flexibility of programmable swi...
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07/21/2022
Templating Shuffles
Cloud data centers are rapidly evolving. At the same time, large-scale d...
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05/18/2022
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL
The performance of reinforcement learning (RL) agents is sensitive to th...
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03/30/2022
Investigating the Properties of Neural Network Representations in Reinforcement Learning
In this paper we investigate the properties of representations learned b...
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11/23/2021
DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning
Self-supervised learning algorithms, including BERT and SimCLR, have ena...
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11/15/2021
Exploiting Action Impact Regularity and Partially Known Models for Offline Reinforcement Learning
Offline reinforcement learning-learning a policy from a batch of data-is...
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10/11/2021
Towards a Cost vs. Quality Sweet Spot for Monitoring Networks
Continuously monitoring a wide variety of performance and fault metrics ...
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10/13/2020
Fault-tolerant and Transactional Stateful Serverless Workflows (extended version)
This paper introduces Beldi, a library and runtime system for writing an...
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07/07/2020
Towards a practical measure of interference for reinforcement learning
Catastrophic interference is common in many network-based learning syste...
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06/02/2020
Performance metrics for intervention-triggering prediction models do not reflect an expected reduction in outcomes from using the model
Clinical researchers often select among and evaluate risk prediction mod...
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07/05/2019
Incrementally Learning Functions of the Return
Temporal difference methods enable efficient estimation of value functio...
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01/06/2019
Recurrent Control Nets for Deep Reinforcement Learning
Central Pattern Generators (CPGs) are biological neural circuits capable...
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11/15/2018
The Utility of Sparse Representations for Control in Reinforcement Learning
We investigate sparse representations for control in reinforcement learn...
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10/20/2018
Attribute-aware Collaborative Filtering: Survey and Classification
Attribute-aware CF models aims at rating prediction given not only the h...
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04/18/2018