Scott Sievert

According to our database, Scott Sievert authored at least 12 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning.

Jifan Zhang, Lalit Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy T. Rogers, Kevin Jamieson, Robert Mankoff, Robert Nowak

CoRR, 2024

2023

Efficiently Learning Relative Similarity Embeddings with Crowdsourcing.

Scott Sievert, Robert D. Nowak, Timothy T. Rogers

J. Open Source Softw., March, 2023

2022

Energy-based Domain Adaption with Active Learning for Emerging Misinformation Detection.

Kyumin Lee, Guanyi Mou, Scott Sievert

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Training machine learning models faster with Dask.

Joesph Holt, Scott Sievert

Proceedings of the 20th Python in Science Conference 2021 (SciPy 2021), Virtual Conference, July 12, 2021

2019

Improving the convergence of SGD through adaptive batch sizes.

Scott Sievert, Zachary Charles

CoRR, 2019

Better and faster hyperparameter optimization with Dask.

Scott Sievert, Tom Augspurger, Matthew Rocklin

Proceedings of the 18th Python in Science Conference 2019 (SciPy 2019), Austin, Texas, July 8, 2019

2018

Altair: Declarative statistical visualization library for Python.

Jacob VanderPlas, Brian E. Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Arvind Satyanarayan, Eitan Lees, Ilia Timofeev, Ben Welsh, Scott Sievert

Dataset, November, 2018

Altair: Declarative statistical visualization library for Python.

Jacob VanderPlas, Brian E. Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Eitan Lees, Ilia Timofeev, Ben Welsh, Scott Sievert

Dataset, November, 2018

Altair: Interactive Statistical Visualizations for Python.

Jacob VanderPlas, Brian E. Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Arvind Satyanarayan, Eitan Lees, Ilia Timofeev, Ben Welsh, Scott Sievert

J. Open Source Softw., 2018

ATOMO: Communication-efficient Learning via Atomic Sparsification.

Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

NEXT: A system to easily connect crowdsourcing and adaptive data collection.

Scott Sievert, Daniel Ross, Lalit Jain, Kevin Jamieson, Robert Nowak, Robert Mankoff

Proceedings of the 16th Python in Science Conference 2017, 2017

2015

The khmer software package: enabling efficient nucleotide sequence analysis.

Michael R. Crusoe, Hussien F. Alameldin, Sherine Awad, Elmar Boucher, Adam Caldwell, Reed Cartwright, Amanda Charbonneau, Bede Constantinides, Greg Edvenson, Scott Fay, Jacob Fenton, Thomas Fenzl, Jordan A. Fish, Leonor Garcia-Gutierrez, Phillip Garland, Jonathan Gluck, Iván González, Sarah Guermond, Jiarong Guo, Aditi Gupta, Joshua R. Herr, Adina Howe, Alex Hyer, Andreas Härpfer, Luiz Irber, Rhys Kidd, David Lin, Justin Lippi, Tamer A. Mansour, Pamela McA'Nulty, Eric McDonald, Jessica Mizzi, Kevin D. Murray, Joshua R. Nahum, Kaben Nanlohy, Alexander Johan Nederbragt, Humberto Ortiz-Zuazaga, Jeramia Ory, Jason Pell, Charles Pepe-Ranney, Zachary N. Russ, Erich M. Schwarz, Camille Scott, Josiah D. Seaman, Scott Sievert, Jared Simpson, Connor Skennerton, James Spencer, Ramakrishnan Srinivasan, Daniel S. Standage, James A. Stapleton, Susan R. Steinman, Joe Stein, Benjamin Taylor, Will Trimble, Heather Wiencko, Michael Wright, Brian Wyss, Qingpeng Zhang, en zyme, C. Titus Brown

F1000Research, 2015