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cs.LG2024★ 2 cited
S7: Selective and Simplified State Space Layers for Sequence Modeling
Taylan Soydan, Nikola Zubić, Nico Messikommer +2
A central challenge in sequence modeling is efficiently handling tasks with extended contexts. While recent state-space models (SSMs) have made significant progress in this area, t…
cs.LG2023
Contrastive Initial State Buffer for Reinforcement Learning
Nico Messikommer, Yunlong Song, Davide Scaramuzza
In Reinforcement Learning, the trade-off between exploration and exploitation poses a complex challenge for achieving efficient learning from limited samples. While recent works ha…