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Asynchronous Stochastic Gradient MCMC with Elastic Coupling
Jost Tobias Springenberg, Aaron Klein, Stefan Falkner +1
We consider parallel asynchronous Markov Chain Monte Carlo (MCMC) sampling for problems where we can leverage (stochastic) gradients to define continuous dynamics which explore the…
A case study of algorithm selection for the traveling thief problem
Markus Wagner, Marius Lindauer, Mustafa Misir +2
Many real-world problems are composed of several interacting components. In order to facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in 2013…
SGDR: Stochastic Gradient Descent with Warm Restarts
Ilya Loshchilov, Frank Hutter
Restart techniques are common in gradient-free optimization to deal with multimodal functions. Partial warm restarts are also gaining popularity in gradient-based optimization to i…
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets
Aaron Klein, Stefan Falkner, Simon Bartels +2
Bayesian optimization has become a successful tool for hyperparameter optimization of machine learning algorithms, such as support vector machines or deep neural networks. Despite…