3 papers
cs.LG2020
Jointly-Learned State-Action Embedding for Efficient Reinforcement Learning
Paul J. Pritz, Liang Ma, Kin K. Leung
While reinforcement learning has achieved considerable successes in recent years, state-of-the-art models are often still limited by the size of state and action spaces. Model-free…
cs.DC2020
Step on the Gas? A Better Approach for Recommending the Ethereum Gas Price
Sam M. Werner, Paul J. Pritz, Daniel Perez
In the Ethereum network, miners are incentivized to include transactions in a block depending on the gas price specified by the sender. The sender of a transaction therefore faces…
cs.DC2020
Fast-Fourier-Forecasting Resource Utilisation in Distributed Systems
Paul J. Pritz, Daniel Perez, Kin K. Leung
Distributed computing systems often consist of hundreds of nodes, executing tasks with different resource requirements. Efficient resource provisioning and task scheduling in such…