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07/07/2023
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Bayesian optimization (BO) is a popular method to optimize costly black-...
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07/08/2020
Auto-Sklearn 2.0: The Next Generation
Automated Machine Learning, which supports practitioners and researchers...
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10/10/2019
Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings
We propose probabilistic models that can extrapolate learning curves of ...
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12/31/2018
Learning to Design RNA
Designing RNA molecules has garnered recent interest in medicine, synthe...
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07/18/2018
Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search
While existing work on neural architecture search (NAS) tunes hyperparam...
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07/04/2018
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
Modern deep learning methods are very sensitive to many hyperparameters,...
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12/02/2016
Asynchronous Stochastic Gradient MCMC with Elastic Coupling
We consider parallel asynchronous Markov Chain Monte Carlo (MCMC) sampli...
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05/23/2016