6 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Enhancing Offline Reinforcement Learning with Curriculum Learning-Based Trajectory Valuation
Amir Abolfazli, Zekun Song, Avishek Anand +1
The success of deep reinforcement learning (DRL) relies on the availability and quality of training data, often requiring extensive interactions with specific environments. In many…
cs.LG2022
Data Valuation for Offline Reinforcement Learning
Amir Abolfazli, Gregory Palmer, Daniel Kudenko
The success of deep reinforcement learning (DRL) hinges on the availability of training data, which is typically obtained via a large number of environment interactions. In many re…
cs.LG2020★ 6 cited
Drift-Aware Multi-Memory Model for Imbalanced Data Streams
Amir Abolfazli, Eirini Ntoutsi
Online class imbalance learning deals with data streams that are affected by both concept drift and class imbalance. Online learning tries to find a trade-off between exploiting pr…