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08/22/2023
FoX: Formation-aware exploration in multi-agent reinforcement learning
Recently, deep multi-agent reinforcement learning (MARL) has gained sign...
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07/25/2023
mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization
Quasi-Newton methods still face significant challenges in training large...
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03/03/2023
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training
Federated Learning (FL) enables collaborations among clients for train m...
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05/02/2022
A Case Study on Parallel HDF5 Dataset Concatenation for High Energy Physics Data Analysis
In High Energy Physics (HEP), experimentalists generate large volumes of...
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01/11/2022
Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits
Local Stochastic Gradient Descent (SGD) with periodic model averaging (F...
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10/19/2021
Layer-wise Adaptive Model Aggregation for Scalable Federated Learning
In Federated Learning, a common approach for aggregating local models ac...
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10/06/2021
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision
Federated Learning (FL) is transforming the ML training ecosystem from a...
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07/29/2019
