Yuanyu Wan

Multi-objective bandits can make finding the best arm *easier* than single-objective settings, even identifying larger optimal sets with fewer samples.

AdamW's second-moment accumulator may obscure its ability to converge under heavy-tailed noise, raising critical questions about its effectiveness in training large language models.