ML Anthology

Optimal Estimation

Jorma Rissanen
ALT 2011 pp. 37
doi:10.1007/978-3-642-24412-4_4 /alt/2011/rissanen2011alt-optimal/

Abstract

Data Y = yt : t = 1, 2, . . ., n , or Y|X = ( y _ t , x _1, t , x _2, t , . . .), X explanatory variables. Want to learn properties in Y expressed by set of distributions as models: f(Y|X_ s ; θ , s ), where θ = θ _1, . . . , θ _ k ( s ) real-valued parameters, s structure parameter: for picking the most important variables in X.

PDF ALT Semantic Scholar

Cite

Text

Rissanen. "Optimal Estimation." International Conference on Algorithmic Learning Theory, 2011. doi:10.1007/978-3-642-24412-4_4

Markdown

[Rissanen. "Optimal Estimation." International Conference on Algorithmic Learning Theory, 2011.](https://mlanthology.org/alt/2011/rissanen2011alt-optimal/) doi:10.1007/978-3-642-24412-4_4

BibTeX

@inproceedings{rissanen2011alt-optimal,
  title     = {{Optimal Estimation}},
  author    = {Rissanen, Jorma},
  booktitle = {International Conference on Algorithmic Learning Theory},
  year      = {2011},
  pages     = {37},
  doi       = {10.1007/978-3-642-24412-4_4},
  url       = {https://mlanthology.org/alt/2011/rissanen2011alt-optimal/}
}