Novel iterative hard-thresholding methods for shallow neural networks simultaneously select features and build predictive models, with a new BIC criterion for high-dimensional settings.
Details: https://www.maxapress.com/article/doi/10.48130/stati-0026-0008
#FeatureSelection #HighDimensional
Novel iterative hard-thresholding methods for shallow neural networks simultaneously select features and build predictive models, with a new BIC criterion for high-dimensional settings.
Details: https://www.maxapress.com/article/doi/10.48130/stati-0026-0008
#FeatureSelection #HighDimensional
Abstract: Model-based reinforcement learning (MBRL) has been used to efficiently solve vision-based control tasks in highdimensional image observations. Although recent MBRL algorithms perform well in trained [1/6 of https://arxiv.org/abs/2506.05419v1]
Abstract: Model-based reinforcement learning (MBRL) has been used to efficiently solve vision-based control tasks in highdimensional image observations. Although recent MBRL algorithms perform well in trained [1/6 of https://arxiv.org/abs/2506.05419v1]
Caspar Schwiedrzik, my supervisor is an absolutely fantastic scientist & an incredible supervisor. I strongly recommend this position & working with him!
Caspar Schwiedrzik, my supervisor is an absolutely fantastic scientist & an incredible supervisor. I strongly recommend this position & working with him!