10 citations · 10 across the 4 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Learning to Order: Task Sequencing as In-Context Optimization
Jan Kobiolka, Christian Frey, Arlind Kadra +2
Task sequencing (TS) is one of the core open problems in Deep Learning, arising in a plethora of real-world domains, from robotic assembly lines to autonomous driving. Unfortunatel…
cs.LG2026
POP: Prior-Fitted First-Order Optimization Policies
Jan Kobiolka, Christian Frey, Gresa Shala +3
Gradient-based optimizers are highly sensitive to design choices in their adaptive learning rate mechanisms. To address this limitation, we introduce POP, a meta-learned Reinforcem…