Zobrazeno 1 - 10
of 24
pro vyhledávání: '"J.. Bagnell"'
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 30
Instrumental variable regression (IVR) is a statistical technique utilized to recover unbiased estimators when there are errors in the independent variables. Estimator bias in learned time series models can yield poor performance in applications such
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 29
How should we gather information to make effective decisions? A classical answer to this fundamental problem is given by the decision-theoretic value of information. Unfortunately, optimizing this objective is intractable, and myopic (greedy) approxi
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 29
Most typical statistical and machine learning approaches to time series modeling optimize a single-step prediction error. In multiple-step simulation, the learned model is iteratively applied, feeding through the previous output as its new input. Any
Autor:
Sue J. Bagnell
The objective of this study was to analyze bibliometric data from ISI, National Institutes of Health (NIH)-funding data, and faculty size information for Association of American Medical Colleges (AAMC) member schools during 1997 to 2007 to assess res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38dacf5bc91e7b23e94da2890f479544
https://europepmc.org/articles/PMC2759161/
https://europepmc.org/articles/PMC2759161/
Publikováno v:
Autonomous Robots; Jul2009, Vol. 27 Issue 1, p25-53, 29p
Autor:
James J. Bagnell, Norman Shachat
Publikováno v:
The Journal of Organic Chemistry. 27:1498-1504
Autor:
Norman Shachat, James J. Bagnell
Publikováno v:
The Journal of Organic Chemistry. 27:471-474
Autor:
Norman Shachat, James J. Bagnell
Publikováno v:
The Journal of Organic Chemistry. 28:991-995
Publikováno v:
The Journal of Organic Chemistry. 26:1987-1990
Publikováno v:
The Journal of Organic Chemistry. 26:1982-1984