3 papers
cs.LG2026
Efficient Long-Horizon Learning for Learned Optimization
Xiaolong Huang, Benjamin Thérien, James Harrison +1
Learned optimization aims to improve upon hand-designed optimizers (e.g., Adam and Muon) by meta-learning small neural network optimizers over a distribution of tasks. While recent…
cs.LG2026
Can Model Merging Improve Aggregation in DiLoCo?
Stefan Horoi, Benjamin Thérien, Guy Wolf +1
Model merging techniques, which aggregate independently finetuned models into one to combine their capabilities, have become a topic of significant interest in recent years, with a…
cs.LG2026
PyLO: Towards Accessible Learned Optimizers in PyTorch
Paul Janson, Benjamin Therien, Quentin Anthony +3
Learned optimizers have been an active research topic over the past decade, with increasing progress toward practical, general-purpose optimizers that can serve as drop-in replacem…