Vincent Liu | DeepAI

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∙ 07/10/2023

Measuring and Mitigating Interference in Reinforcement Learning

Catastrophic interference is common in many network-based learning syste...

0 Vincent Liu, et al. ∙

∙ 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...

1 Vincent Liu, et al. ∙

∙ 07/26/2022

FP4: Line-rate Greybox Fuzz Testing for P4 Switches

Compared to fixed-function switches, the flexibility of programmable swi...

0 Nofel Yaseen, et al. ∙

∙ 07/21/2022

Templating Shuffles

Cloud data centers are rapidly evolving. At the same time, large-scale d...

0 Qizhen Zhang, et al. ∙

∙ 05/18/2022

No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL

The performance of reinforcement learning (RL) agents is sensitive to th...

0 Han Wang, et al. ∙

∙ 03/30/2022

Investigating the Properties of Neural Network Representations in Reinforcement Learning

In this paper we investigate the properties of representations learned b...

26 Han Wang, et al. ∙

∙ 11/23/2021

DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning

Self-supervised learning algorithms, including BERT and SimCLR, have ena...

0 Alex Tamkin, et al. ∙

∙ 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...

0 Vincent Liu, et al. ∙

∙ 10/11/2021

Towards a Cost vs. Quality Sweet Spot for Monitoring Networks

Continuously monitoring a wide variety of performance and fault metrics ...

0 Nofel Yaseen, et al. ∙

∙ 10/13/2020

Fault-tolerant and Transactional Stateful Serverless Workflows (extended version)

This paper introduces Beldi, a library and runtime system for writing an...

0 Haoran Zhang, et al. ∙

∙ 07/07/2020

Towards a practical measure of interference for reinforcement learning

Catastrophic interference is common in many network-based learning syste...

28 Vincent Liu, et al. ∙

∙ 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...

4 Alejandro Schuler, et al. ∙

∙ 07/05/2019

Incrementally Learning Functions of the Return

Temporal difference methods enable efficient estimation of value functio...

0 Brendan Bennett, et al. ∙

∙ 01/06/2019

Recurrent Control Nets for Deep Reinforcement Learning

Central Pattern Generators (CPGs) are biological neural circuits capable...

0 Vincent Liu, et al. ∙

∙ 11/15/2018

The Utility of Sparse Representations for Control in Reinforcement Learning

We investigate sparse representations for control in reinforcement learn...

4 Vincent Liu, et al. ∙

∙ 10/20/2018

Attribute-aware Collaborative Filtering: Survey and Classification

Attribute-aware CF models aims at rating prediction given not only the h...

0 Wen-Hao Chen, et al. ∙

∙ 04/18/2018

Volur: Concurrent Edge/Core Route Control in Data Center Networks

A perennial question in computer networks is where to place functionalit...

0 Qiao Zhang, et al. ∙

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