6 citations · 14 across the 6 of their papers we have counts for
7 papers
Personalized Federated Reinforcement Learning via Model-Agnostic Meta-Learning: Convergence of Exact and Hessian-Free Meta-Policy Gradients
Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon
We study personalized federated reinforcement learning, in which agents, each acting in its own Markov decision process, collaborate through a server to learn a shared MAML-sty…
SurvCF(t): Counterfactual Explanations for Survival Analysis in Predictive Maintenance Multivariate Time Series Data
Zara Karazian, Panagiotis Papapetrou, Sindri Magnússon +2
Predictive maintenance relies on accurate Remaining Useful Life estimation, often formulated using survival analysis over multivariate time-series data. While modern deep survival…
Compressed Federated Reinforcement Learning with a Generative Model
Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon
Reinforcement learning has recently gained unprecedented popularity, yet it still grapples with sample inefficiency. Addressing this challenge, federated reinforcement learning (Fe…
On the Convergence of Federated Learning Algorithms without Data Similarity
Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon
Data similarity assumptions have traditionally been relied upon to understand the convergence behaviors of federated learning methods. Unfortunately, this approach often demands fi…
Parallel Momentum Methods Under Biased Gradient Estimations
Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon
Parallel stochastic gradient methods are gaining prominence in solving large-scale machine learning problems that involve data distributed across multiple nodes. However, obtaining…
A Cost-Sensitive Transformer Model for Prognostics Under Highly Imbalanced Industrial Data
Ali Beikmohammadi, Mohammad Hosein Hamian, Neda Khoeyniha +3
The rapid influx of data-driven models into the industrial sector has been facilitated by the proliferation of sensor technology, enabling the collection of vast quantities of data…
SCANIA Component X Dataset: A Real-World Multivariate Time Series Dataset for Predictive Maintenance
Zahra Kharazian, Tony Lindgren, Sindri Magnússon +2
Predicting failures and maintenance time in predictive maintenance is challenging due to the scarcity of comprehensive real-world datasets, and among those available, few are of ti…