#hyperparameters — Public Fediverse posts

'Empirical Design in Reinforcement Learning', by Andrew Patterson, Samuel Neumann, Martha White, Adam White.

http://jmlr.org/papers/v25/23-0183.html

#reinforcement #experiments #hyperparameters

'Pre-trained Gaussian Processes for Bayesian Optimization', by Zi Wang et al.

http://jmlr.org/papers/v25/23-0269.html

#priors #prior #hyperparameters

'Low-rank Variational Bayes correction to the Laplace method', by Janet van Niekerk, Haavard Rue.

http://jmlr.org/papers/v25/21-1405.html

#variational #hyperparameters #approximations

'Beyond the Golden Ratio for Variational Inequality Algorithms', by Ahmet Alacaoglu, Axel Böhm, Yura Malitsky.

http://jmlr.org/papers/v24/22-1488.html

#ascent #constrained #hyperparameters

'Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching', by Eliezer de Souza da Silva, Tomasz Kuśmierczyk, Marcelo Hartmann, Arto Klami.

http://jmlr.org/papers/v24/21-0623.html

#factorization #hyperparameters #priors