AdaGeo: Adaptive geometric learning for optimization and sampling
Gradient-based optimization and Markov Chain Monte Carlo sampling can be found at the heart of a multitude of machine learning methods. In high-dimensional settings, well-known issues such as slow-mixing, non-convexity and correlations can hinder the algorithms’ efficiency. In order to overcome thes...
Huvudupphovsmän: | Abbati, G, Tosi, A, Osborne, M, Flaxman, S |
---|---|
Materialtyp: | Conference item |
Publicerad: |
Proceedings of Machine Learning Research
2018
|
Liknande verk
Liknande verk
-
Geo-metrics : the metric application of geometric tolerancing/
av: 429133 Foster, Lowell W.
Publicerad: (1974) -
On Using GeoGebra and ChatGPT for Geometric Discovery
av: Francisco Botana, et al.
Publicerad: (2024-07-01) -
Ada madu ada racun /
av: Adnil Zaff, author
Publicerad: (2013) -
AdaCB: An Adaptive Gradient Method with Convergence Range Bound of Learning Rate
av: Xuanzhi Liao, et al.
Publicerad: (2022-09-01) -
Kejap ada kejap tak ada /
av: Ebriza Md. Aminnudin, 1977- author
Publicerad: (2013)