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cs.LG2020
Adam with Bandit Sampling for Deep Learning
Rui Liu, Tianyi Wu, Barzan Mozafari
Adam is a widely used optimization method for training deep learning models. It computes individual adaptive learning rates for different parameters. In this paper, we propose a ge…
cs.DB2020★ 4 cited
Joins on Samples: A Theoretical Guide for Practitioners
Dawei Huang, Dong Young Yoon, Seth Pettie +1
Despite decades of research on approximate query processing (AQP), our understanding of sample-based joins has remained limited and, to some extent, even superficial. The common be…