MLPerf Training Benchmark. - Peter Mattson; Christine Cheng; Cody Coleman; Greg Diamos; Paulius Micikevicius; David A. Patterson 001; Hanlin Tang; Gu-Yeon Wei; Peter Bailis; Victor Bittorf; David Brooks 001; Dehao Chen; et al. (CoRR, 2019)

Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. - Cody Coleman; Daniel Kang; Deepak Narayanan; Luigi Nardi; Tian Zhao 001; Jian Zhang 049; Peter Bailis; Kunle Olukotun; Christopher Ré; Matei Zaharia (ACM SIGOPS Oper. Syst. Rev., 2019)

Selection via Proxy: Efficient Data Selection for Deep Learning. - Cody Coleman; Christopher Yeh; Stephen Mussmann; Baharan Mirzasoleiman; Peter Bailis; Percy Liang; Jure Leskovec; Matei Zaharia (ICLR, 2020)

MLPerf Inference Benchmark. - Vijay Janapa Reddi; Christine Cheng; David Kanter; Peter Mattson; Guenther Schmuelling; Carole-Jean Wu; Brian Anderson; Maximilien Breughe; Mark Charlebois; William Chou; Ramesh Chukka; Cody Coleman; et al. (ISCA, 2020)

MLPerf Training Benchmark. - Peter Mattson; Christine Cheng; Gregory F. Diamos; Cody Coleman; Paulius Micikevicius; David A. Patterson 001; Hanlin Tang; Gu-Yeon Wei; Peter Bailis; Victor Bittorf; David Brooks 001; Dehao Chen; et al. (MLSys, 2020)

Similarity Search for Efficient Active Learning and Search of Rare Concepts. - Cody Coleman; Edward Chou; Sean Culatana; Peter Bailis; Alexander C. Berg; Roshan Sumbaly; Matei Zaharia; I. Zeki Yalniz (CoRR, 2020)

MLPerf: An Industry Standard Benchmark Suite for Machine Learning Performance. - Peter Mattson; Hanlin Tang; Gu-Yeon Wei; Carole-Jean Wu; Vijay Janapa Reddi; Christine Cheng; Cody Coleman; Greg Diamos; David Kanter; Paulius Micikevicius; David A. Patterson 001; Guenther Schmuelling (IEEE Micro, 2020)

Leveraging Big Data to Discover High Yield Prognostics Applications. - Cody Coleman; Yi Zhang; Maria Seale (ICPHM, 2021)

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Srini Bala; Daniel J. Beutel; Victor Bittorf; Akshay Chaudhari; Alexander Chowdhury; Cody Coleman; Bala Desinghu; et al. (CoRR, 2021)

Resource and data efficient deep learning. - Cody Coleman (2021)

Similarity Search for Efficient Active Learning and Search of Rare Concepts. - Cody Coleman; Edward Chou; Julian Katz-Samuels; Sean Culatana; Peter Bailis; Alexander C. Berg; Robert D. Nowak; Roshan Sumbaly; Matei Zaharia; I. Zeki Yalniz (AAAI, 2022)

The Dollar Street Dataset: Images Representing the Geographic and Socioeconomic Diversity of the World. - William Gaviria Rojas; Sudnya Frederick Diamos; Keertan Kini; David Kanter; Vijay Janapa Reddi; Cody Coleman (NeurIPS, 2022)

DataPerf: Benchmarks for Data-Centric AI Development. - Mark Mazumder; Colby R. Banbury; Xiaozhe Yao; Bojan Karlas; William Gaviria Rojas; Sudnya Frederick Diamos; Greg Diamos; Lynn He; Douwe Kiela; David Jurado; David Kanter; Rafael Mosquera; et al. (CoRR, 2022)

DataPerf: Benchmarks for Data-Centric AI Development. - Mark Mazumder; Colby R. Banbury; Xiaozhe Yao; Bojan Karlas; William Gaviria Rojas; Sudnya Frederick Diamos; Greg Diamos; Lynn He; Alicia Parrish; Hannah Rose Kirk; Jessica Quaye; Charvi Rastogi; et al. (NeurIPS, 2023)

DMLR: Data-centric Machine Learning Research - Past, Present and Future. - Luis Oala; Manil Maskey; Lilith Bat-Leah; Alicia Parrish; Nezihe Merve Gürel; Tzu-Sheng Kuo; Yang Liu 018; Rotem Dror; Danilo Brajovic; Xiaozhe Yao; Max Bartolo; William Gaviria Rojas; et al. (CoRR, 2023)

Federated benchmarking of medical artificial intelligence with MedPerf. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Anna Wuest; Sarthak Pati; Hasan Kassem; Maximilian Zenk; Ujjwal Baid; Prakash Narayana Moorthy; Alexander Chowdhury; et al. (Nat. Mac. Intell., 2023)

Introducing v0.5 of the AI Safety Benchmark from MLCommons. - Bertie Vidgen; Adarsh Agrawal; Ahmed M. Ahmed 004; Victor Akinwande; Namir Al-Nuaimi; Najla Alfaraj; Elie Alhajjar; Lora Aroyo; Trupti Bavalatti; Borhane Blili-Hamelin; Kurt D. Bollacker; Rishi Bomassani; et al. (CoRR, 2024)

AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons. - Shaona Ghosh; Heather Frase; Adina Williams; Sarah Luger; Paul Röttger; Fazl Barez; Sean McGregor; Kenneth Fricklas; Mala Kumar; Quentin Feuillade-Montixi; Kurt Bollacker; Felix Friedrich; et al. (CoRR, 2025)