2 papers
cs.AI2026
Dynamic Context Scheduling: Learning Beyond the Static Universe
Martin Mráz, André Biedenkapp
We study dynamic context scheduling as a training instrument for contextual re- inforcement learning. Rather than treating intra-episode context variation as a deployment reality,…
cs.LG2026
TimEE: End-to-end Time Series Classification via In-Context Learning
Jaris Küken, Shi Bin Hoo, Martin Mráz +2
Time series classification (TSC) is dominated by a two-stage paradigm: train a feature encoder -- either from scratch on the target dataset or via pretraining on large corpora -- a…