InfoQ

Enhancing A/B Testing at DoorDash with Multi-Armed Bandits

While experimentation is essential, traditional A/B testing can be excessively slow and expensive, according to DoorDash engineers Caixia Huang and Alex Weinstein. To address these limitations, they ...
IEEE

Spreeze: High-Throughput Parallel Reinforcement Learning Framework

Abstract: The promotion of large-scale applications of reinforcement learning (RL) requires efficient training computation. While existing parallel RL frameworks encompass a variety of RL algorithms ...
IEEE

PS-DFL: A Parallel Sequential Decentralized Federated Learning Framework to Facilitate DGA Interpretation Related to Transformer Fault Diagnosis

Abstract: Recently, data-driven methods have demonstrated excellent performance in diagnosing faults in power transformers. However, concerns about data privacy and computational resources arise due ...