OpenAlex | Reconciling modern machine-learning practice and the classical bias

Reconciling modern machine-learning practice and the classical bias–variance trade-off

Work

Year: 2019

Type: article

Abstract: Breakthroughs in machine learning are rapidly changing science and society, yet our fundamental understanding of this technology has lagged far behind. Indeed, one of the central tenets of the field, ... more

Source: Proceedings of the National Academy of Sciences

Authors Mikhail Belkin, Daniel Hsu, Siyuan Ma, Soumik Mandal

Institutions The Ohio State University, Columbia University

Cites: 35

Cited by: 1,208

Related to: 10

FWCI: 101

Citation percentile (by year/subfield): 100

Topic: Machine Learning and Data Classification

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders National Science Foundation, Alfred P. Sloan Foundation

Grant IDS CCF-1740833, FG-2016-6295