I am a PhD student at UC Berkeley studying machine learning under Joseph Gonzalez
[arxiv, ICML, PDF] Daniel Rothchild,* Ashwinee Panda,* Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora “FetchSGD: Communication-Efficient Federated Learning with Sketching.” ICML, 2020
[arxiv, PDF] Bohan Zhai,* Tianren Gao,* Flora Xue,* Daniel Rothchild, Bichen Wu, Joseph E. Gonzalez, Kurt Keutzer. “SqueezeWave: Extremely Lightweight Vocoders for On-device Speech Synthesis.” 2020.
[arxiv, PDF, NeurIPS] Nikita Ivkin*, Daniel Rothchild*, Enayat Ullah*, Vladimir Braverman, Ion Stoica, Raman Arora. “Communication-Efficient Distributed SGD with Sketching.” NeurIPS, 2019.
[arxiv, PDF, PASP] Daniel Rothchild, Christopher Stubbs, Peter Yoachim. “ALTSched: Improved Scheduling for Time-Domain Science with LSST.” PASP, 2019.
[PDF, A&A] Simon Huber, Sherry Suyu, Ulrich Nöbauer, Vivien Bonvin, Daniel Rothchild, James Hung-Hsu Chan, Humna Awan, Frederic Courbin, Markus Kromer, Phil Marshall, Masamune Oguri, Tiago Ribeiro, LSST DESC. “Strongly lensed SNe Ia in the era of LSST: observing cadence for lens discoveries and time-delay measurements.” Astronomy and Astrophysics, 2019.
[arxiv, PDF] Michelle Lochner, Daniel Scolnic, et al. “Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey.” 2018.
[arxiv, PDF] Daniel Scolnic, Michelle Lochner, et al. “Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Deep Drilling Fields and other Special Programs.” 2018.
[PDF, SRC] Daniel Rothchild and Stuart Shieber. “Automatically Determining Versions of Scholarly Articles.” Scholarly and Research Communication, 2017.
[PDF, TS] Daniel Rothchild. “Finding Fraudulent Websites Using Twitter Streams.” Technology Science, 2015.
(page last updated April 2020)