3 papers
cs.HC2020
HyperTendril: Visual Analytics for User-Driven Hyperparameter Optimization of Deep Neural Networks
Heungseok Park, Yoonsoo Nam, Ji-Hoon Kim +1
To mitigate the pain of manually tuning hyperparameters of deep neural networks, automated machine learning (AutoML) methods have been developed to search for an optimal set of hyp…
cs.LG2018
CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms
Jinwoong Kim, Minkyu Kim, Heungseok Park +6
Many hyperparameter optimization (HyperOpt) methods assume restricted computing resources and mainly focus on enhancing performance. Here we propose a novel cloud-based HyperOpt (C…
cs.DC2018
NSML: Meet the MLaaS platform with a real-world case study
Hanjoo Kim, Minkyu Kim, Dongjoo Seo +9
The boom of deep learning induced many industries and academies to introduce machine learning based approaches into their concern, competitively. However, existing machine learning…