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20162020
most citedClassifying Variable-Length Audio Files with All-Convolutional Networks and Masked Global Pooling

12 citations · 19 across the 3 of their papers we have counts for

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cs.LG2020★ 4 cited

Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning

Lars Hertel, Pierre Baldi, Daniel L. Gillen

Reinforcement learning algorithms can show strong variation in performance between training runs with different random seeds. In this paper we explore how this affects hyperparamet…

cs.LG2020

Sherpa: Robust Hyperparameter Optimization for Machine Learning

Lars Hertel, Julian Collado, Peter Sadowski +2

Sherpa is a hyperparameter optimization library for machine learning models. It is specifically designed for problems with computationally expensive, iterative function evaluations…