A Very Brief and Critical Discussion on AutoML

2018/11/09 by Bin Liu, Liu, Bin · 2 citations
Computer Science · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning and Algorithms #Machine Learning and Data Classification #cs.AI

paper · pdf · doi:10.48550/arxiv.1811.03822

5 pages

arxiv created 2018/11/09 · openalex publication_date 2018/11/09 · arxiv updated 2018/11/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This contribution presents a very brief and critical discussion on automated machine learning (AutoML), which is categorized here into two classes, referred to as narrow AutoML and generalized AutoML, respectively. The conclusions yielded from this discussion can be summarized as follows: (1) most existent research on AutoML belongs to the class of narrow AutoML; (2) advances in narrow AutoML are mainly motivated by commercial needs, while any possible benefit obtained is definitely at a cost of increase in computing burdens; (3)the concept of generalized AutoML has a strong tie in spirit with artificial general intelligence (AGI), also called "strong AI", for which obstacles abound for obtaining pivotal progresses.

Citations

• Taking the Human Out of the Loop: A Review of Bayesian Optimization
• Automating biomedical data science through tree-based pipeline optimization

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