most citedBOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2023

Adaptive Sampling for Deep Learning via Efficient Nonparametric Proxies

Shabnam Daghaghi, Benjamin Coleman, Benito Geordie +1

Data sampling is an effective method to improve the training speed of neural networks, with recent results demonstrating that it can even break the neural scaling laws. These resul…

cs.LG2023★ 1 cited

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware

Nicholas Meisburger, Vihan Lakshman, Benito Geordie +9

Efficient large-scale neural network training and inference on commodity CPU hardware is of immense practical significance in democratizing deep learning (DL) capabilities. Present…