no code implementations • ICML 2020 • Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Vladimir Braverman, Joseph Gonzalez, Ion Stoica, Raman Arora
A key insight in the design of FedSketchedSGD is that, because the Count Sketch is linear, momentum and error accumulation can both be carried out within the sketch.
no code implementations • 2 Nov 2023 • Daniel Rothchild, Andrew S. Rosen, Eric Taw, Connie Robinson, Joseph E. Gonzalez, Aditi S. Krishnapriyan
We present an investigation into diffusion models for molecular generation, with the aim of better understanding how their predictions compare to the results of physics-based calculations.
no code implementations • 11 Apr 2022 • David Patterson, Joseph Gonzalez, Urs Hölzle, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, Jeff Dean
Four best practices can reduce ML training energy by up to 100x and CO2 emissions up to 1000x.
1 code implementation • 23 Aug 2021 • Daniel Rothchild, Alex Tamkin, Julie Yu, Ujval Misra, Joseph Gonzalez
Methods for designing organic materials with desired properties have high potential impact across fields such as medicine, renewable energy, petrochemical engineering, and agriculture.
no code implementations • 21 Apr 2021 • David Patterson, Joseph Gonzalez, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, Jeff Dean
To help reduce the carbon footprint of ML, we believe energy usage and CO2e should be a key metric in evaluating models, and we are collaborating with MLPerf developers to include energy usage during training and inference in this industry standard benchmark.
no code implementations • 15 Jul 2020 • Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora
A key insight in the design of FetchSGD is that, because the Count Sketch is linear, momentum and error accumulation can both be carried out within the sketch.
1 code implementation • 16 Jan 2020 • Bohan Zhai, Tianren Gao, Flora Xue, Daniel Rothchild, Bichen Wu, Joseph E. Gonzalez, Kurt Keutzer
Automatic speech synthesis is a challenging task that is becoming increasingly important as edge devices begin to interact with users through speech.
Sound Audio and Speech Processing
2 code implementations • NeurIPS 2019 • Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora
Large-scale distributed training of neural networks is often limited by network bandwidth, wherein the communication time overwhelms the local computation time.