68 citations · 175 across the 10 of their papers we have counts for
4 papers · 1 filter
Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems
Laurel Orr, Atindriyo Sanyal, Xiao Ling +2
The industrial machine learning pipeline requires iterating on model features, training and deploying models, and monitoring deployed models at scale. Feature stores were developed…
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps
Tri Dao, Nimit S. Sohoni, Albert Gu +5
Modern neural network architectures use structured linear transformations, such as low-rank matrices, sparse matrices, permutations, and the Fourier transform, to improve inference…
Low-Memory Neural Network Training: A Technical Report
Nimit S. Sohoni, Christopher R. Aberger, Megan Leszczynski +2
Memory is increasingly often the bottleneck when training neural network models. Despite this, techniques to lower the overall memory requirements of training have been less widely…
High-Accuracy Low-Precision Training
Christopher De Sa, Megan Leszczynski, Jian Zhang +4
Low-precision computation is often used to lower the time and energy cost of machine learning, and recently hardware accelerators have been developed to support it. Still, it has b…