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stat.ML2024
Tamed Langevin sampling under weaker conditions
Iosif Lytras, Panayotis Mertikopoulos
Motivated by applications to deep learning which often fail standard Lipschitz smoothness requirements, we examine the problem of sampling from distributions that are not log-conca…
stat.ML2020★ 5 cited
A new regret analysis for Adam-type algorithms
Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos +1
In this paper, we focus on a theory-practice gap for Adam and its variants (AMSgrad, AdamNC, etc.). In practice, these algorithms are used with a constant first-order moment parame…