Embrace open-environment machine learning for robust AI

doi:10.1093/nsr/nwad300

2023-11-28

李罡 (Gang Li) *

Aswani Kumar Cherukuri

DOI：10.1093/nsr/nwad300

原文链接

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摘要

En 中文

Dive into the novel OpenML paradigm, unveiling its transformative approach to robust AI in dynamic environment, shaping Automated Machine Learning with adaptability for ground breaking advancements towards Artificial General Intelligence.

Keyword:

open-environment machine learning

artificial general intelligence

automated machine learning

robust AI

AI总结

对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

National Science Review

IF:

17.1

论文数:

3.8K

被引数:

2.0W

机构

Deakin University

学者数:

2.0W

论文数: 2.1W

被引数: 2.8W

引用论文

NMR study of the interaction of plastocyanin with chromium(III) analogues of inorganic electron transfer reagents

Biochimica et Biophysica Acta (BBA) - Bioenergetics

IF0

1980-06-01

PREAI

David J. Cookson; Mark T. Hayes; Peter E. Wright

AutoML: A survey of the state-of-the-art AutoML: 对最新技术的调查

KNOWLEDGE-BASED SYSTEMS

IF7.6

2021-01-01

857

OAAI

He, Xin; Zhao, Kaiyong; Chu, Xiaowen

Open-environment machine learning 开放环境机器学习

NATIONAL SCIENCE REVIEW

IF17.1

2022-07-01

OAAI

Zhou, Zhi-Hua

Structure and microwave dielectric properties of BaLa₄Ti₄O₁₅

Journal of Physics: Condensed Matter

IF0

2006-07-21

PREAI

H Zheng; D I Woodward; L Gillie; I M Reaney

Effect of earthworms on grassland on recently reclaimed polder soils in the Netherlands

Earthworm Ecology

IF0

1983-01-01

PREAI

M. Hoogerkamp; H. Rogaar; H. J. P. Eijsackers