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cs.LG2025
Detecting Model Drifts in Non-Stationary Environment Using Edit Operation Measures
Chang-Hwan Lee, Alexander Shim
Reinforcement learning (RL) agents typically assume stationary environment dynamics. Yet in real-world applications such as healthcare, robotics, and finance, transition probabilit…
cs.LG2022
A Probabilistic Interpretation of Transformers
Alexander Shim
We propose a probabilistic interpretation of exponential dot product attention of transformers and contrastive learning based off of exponential families. The attention sublayer of…