research
∙
02/04/2023
Locally Constrained Policy Optimization for Online Reinforcement Learning in Non-Stationary Input-Driven Environments
We study online Reinforcement Learning (RL) in non-stationary input-driv...
share
research
∙
01/14/2022
Reinforcement Learning in Time-Varying Systems: an Empirical Study
Recent research has turned to Reinforcement Learning (RL) to solve chall...
research
∙
02/17/2019
Conclave: secure multi-party computation on big data (extended TR)
Secure Multi-Party Computation (MPC) allows mutually distrusting parties...
research
∙
12/06/2018
K-Pg: Shared State in Differential Dataflows
Many of the most popular scalable data-processing frameworks are fundame...
research
∙
10/03/2018
Learning Scheduling Algorithms for Data Processing Clusters
Efficiently scheduling data processing jobs on distributed compute clust...
research
∙
07/06/2018
Variance Reduction for Reinforcement Learning in Input-Driven Environments
We consider reinforcement learning in input-driven environments, where a...
research
∙
09/14/2017