Meta-learning from learning curves for budget-limited algorithm selection
Training a large set of machine learning algorithms to convergence in order to select the
best-performing algorithm for a dataset is computationally wasteful. Moreover, in a budget …
best-performing algorithm for a dataset is computationally wasteful. Moreover, in a budget …
GreedyAgent: Crafting Efficient Agents for Meta-learning from Learning Curves via Greedy Algorithm Selection
J He, X Song, X Yan, N Wang, Y Miao, Z Jiang… - … on Intelligent Computing, 2024 - Springer
With the rapid development of artificial intelligence and machine learning technologies,
Automated Machine Learning (AutoML) has become a hot research area in recent years …
Automated Machine Learning (AutoML) has become a hot research area in recent years …
Methodology for Design and Analysis of Machine Learning Competitions
A Pavão - 2023 - inria.hal.science
We develop and study a systematic and unified methodology to organize and use scientific
challenges in research, particularly in the domain of machine learning (data-driven artificial …
challenges in research, particularly in the domain of machine learning (data-driven artificial …
[PDF][PDF] de Compétitions en Apprentissage Automatique
A PAVÃO - 2023 - adrienpavao.com
We develop and study a systematic and unified methodology to organize and use scientific
challenges in research, particularly in the domain of machine learning (data-driven artificial …
challenges in research, particularly in the domain of machine learning (data-driven artificial …
Special designs and competition protocols
With the development of AI technology, many novel machine learning frameworks have
been raised and applied in AI academic and industry research and business application …
been raised and applied in AI academic and industry research and business application …