#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

#CausalML update - I am now fitting my first #CausalForest on real data!

Does anyone have advice on the most important #hyperparameters (After the # of trees & tree depth.)

I'm working on large imbalanced data sets and a large number of treatment variables, so it's not like anything you see in the economics literature. 🤔 #ML #AI #causal

'On the Hyperparameters in Stochastic Gradient Descent with Momentum', by Bin Shi.

http://jmlr.org/papers/v25/22-1189.html

#sgd #hyperparameters #stochastic

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

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

#priors #prior #hyperparameters

'An Algorithmic Framework for the Optimization of Deep Neural Networks Architectures and Hyperparameters', by Julie Keisler, El-Ghazali Talbi, Sandra Claudel, Gilles Cabriel.

http://jmlr.org/papers/v25/23-0166.html

#forecasting #algorithmic #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

Computationally-efficient initialisation of GPs: The generalised variogram method

Felipe Tobar, Elsa Cazelles, Taco de Wolff

Action editor: Cédric Archambeau.

https://openreview.net/forum?id=slsAQHpS7n

#gps #geostatistics #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

On my blog: Optimizing Generative AI for Question Answering

#AI #FoundationModels #Decoders #Encoders #Experiments #HyperParameters

https://heidloff.net/article/optimizing-generative-ai-for-question-answering/

No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL

Han Wang, Archit Sakhadeo, Adam M White et al.

https://openreview.net/forum?id=AiOUi3440V

#hyperparameters #hyperparameter #learns

What are you using to tune your #hyperparameters? As #AutoML researchers, it is very important for us to understand the needs and expectations of ML researchers, engineers and data scientists. Help us and yourself by being part of the following survey https://www.soscisurvey.de/hpo-method-validation/

Is there a #julialang equivalent of https://github.com/google/gin-config ?

I found using .gin files a really simple but useful way to store #hyperparameters during #deeplearning

If you do #machinelearning with #python and haven't heard of it, check it out!