20 citations · 41 across the 5 of their papers we have counts for
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cs.LG2023★ 18 cited
Probabilistic Neural Data Fusion for Learning from an Arbitrary Number of Multi-fidelity Data Sets
Carlos Mora, Jonathan Tammer Eweis-Labolle, Tyler Johnson +2
In many applications in engineering and sciences analysts have simultaneous access to multiple data sources. In such cases, the overall cost of acquiring information can be reduced…
cs.LG2020★ 20 cited
AdaScale SGD: A User-Friendly Algorithm for Distributed Training
Tyler B. Johnson, Pulkit Agrawal, Haijie Gu +1
When using large-batch training to speed up stochastic gradient descent, learning rates must adapt to new batch sizes in order to maximize speed-ups and preserve model quality. Re-…