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Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems

Aug 11, 2021
Laurel Orr, Atindriyo Sanyal, Xiao Ling, Karan Goel, Megan Leszczynski

* VLDB 2021 

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Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps

Jan 05, 2021
Tri Dao, Nimit S. Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré

* International Conference on Learning Representations (ICLR) 2020 spotlight 

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Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation

Oct 23, 2020
Laurel Orr, Megan Leszczynski, Simran Arora, Sen Wu, Neel Guha, Xiao Ling, Christopher Re

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Understanding the Downstream Instability of Word Embeddings

Feb 29, 2020
Megan Leszczynski, Avner May, Jian Zhang, Sen Wu, Christopher R. Aberger, Christopher Ré

* In Proceedings of the 3rd MLSys Conference, 2020 

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Low-Memory Neural Network Training: A Technical Report

Apr 24, 2019
Nimit Sharad Sohoni, Christopher Richard Aberger, Megan Leszczynski, Jian Zhang, Christopher Ré

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High-Accuracy Low-Precision Training

Mar 09, 2018
Christopher De Sa, Megan Leszczynski, Jian Zhang, Alana Marzoev, Christopher R. Aberger, Kunle Olukotun, Christopher Ré

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