arXiv:1903.05263
AutoML @ NeurIPS 2018 challenge: Design and Results
원문 초록
We organized a competition on Autonomous Lifelong Machine Learning with Drift that was part of the competition program of NeurIPS 2018. This data driven competition asked participants to develop computer programs capable of solving supervised learning problems where the i.i.d. assumption did not hold. Large data sets were arranged in a lifelong learning and evaluation scenario and CodaLab was used as the challenge platform. The challenge attracted more than 300 participants in its two month duration. This chapter describes the design of the challenge and summarizes its main results.
함께 살펴볼 논문
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Neuraxle - A Python Framework for Neat Machine Learning Pipelines
ATM: A distributed, collaborative, scalable system for automated machine learning
Overtuning in Hyperparameter Optimization
From Tiny Machine Learning to Tiny Deep Learning: A Survey
Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning
VirnyFlow: A Design Space for Responsible Model Development
토론
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