most citedA Data-Centric Approach for Training Deep Neural Networks with Less Data

8 citations · 8 across the 2 of their papers we have counts for

collaborators

2 papers

cs.DC2023

CODAG: Characterizing and Optimizing Decompression Algorithms for GPUs

Jeongmin Park, Zaid Qureshi, Vikram Mailthody +10

Data compression and decompression have become vital components of big-data applications to manage the exponential growth in the amount of data collected and stored. Furthermore, b…

cs.AI2021★ 8 cited

A Data-Centric Approach for Training Deep Neural Networks with Less Data

Mohammad Motamedi, Nikolay Sakharnykh, Tim Kaldewey

While the availability of large datasets is perceived to be a key requirement for training deep neural networks, it is possible to train such models with relatively little data. Ho…