no code implementations • 8 Apr 2024 • Taiyi Wang, Eiko Yoneki
This study introduces the Instance-Aware Index Advisor (IA2), a novel deep reinforcement learning (DRL)-based approach for optimizing index selection in databases facing large action spaces of potential candidates.
1 code implementation • 2 Jan 2022 • Hao Sun, Taiyi Wang
Although it is well known that exploration plays a key role in Reinforcement Learning (RL), prevailing exploration strategies for continuous control tasks in RL are mainly based on naive isotropic Gaussian noise regardless of the causality relationship between action space and the task and consider all dimensions of actions equally important.
no code implementations • 29 Jun 2020 • Ali Hadian, Behzad Ghaffari, Taiyi Wang, Thomas Heinis
The initial work on learned indexes has shown that by learning the cumulative distribution function of the data, index structures such as the B-Tree can improve their performance by one order of magnitude while having a smaller memory footprint.