activity
20162026
most citedMedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation

173 citations · 796 across the 78 of their papers we have counts for

collaborators
Showing 2021 · cs.LGShow all

6 papers · 2 filters

cs.LG2021★ 6 cited

The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage

Daniel Galvez, Greg Diamos, Juan Ciro +7

The People's Speech is a free-to-download 30,000-hour and growing supervised conversational English speech recognition dataset licensed for academic and commercial usage under CC-B…

cs.LG2021★ 173 cited

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation

Alexandros Karargyris, Renato Umeton, Micah J. Sheller +39

Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving prov…

cs.LG2021

Widening Access to Applied Machine Learning with TinyML

Vijay Janapa Reddi, Brian Plancher, Susan Kennedy +21

Broadening access to both computational and educational resources is critical to diffusing machine-learning (ML) innovation. However, today, most ML resources and experts are siloe…

cs.LG2021★ 2 cited

MLPerf Tiny Benchmark

Colby Banbury, Vijay Janapa Reddi, Peter Torelli +19

Advancements in ultra-low-power tiny machine learning (TinyML) systems promise to unlock an entirely new class of smart applications. However, continued progress is limited by the…

cs.LG2021★ 4 cited

RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads

James Gleeson, Srivatsan Krishnan, Moshe Gabel +3

Deep reinforcement learning (RL) has made groundbreaking advancements in robotics, data center management and other applications. Unfortunately, system-level bottlenecks in RL work…

cs.LG2021★ 5 cited

Data Engineering for Everyone

Vijay Janapa Reddi, Greg Diamos, Pete Warden +2

Data engineering is one of the fastest-growing fields within machine learning (ML). As ML becomes more common, the appetite for data grows more ravenous. But ML requires more data…