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Online action learning in high dimensions: a new exploration rule for contextual et-greedy heuristics

Flores, Claudio C.; Medeiros, Marcelo C. - 2020

Bandit problems are pervasive in various fields of research and are also present in several practical applications … one of the most popular bandit solutions, the original et-greedy heuristics, to high-dimensional contexts. Moreover, we … range of exploration of new actions. We find reasonable bounds for the cumulative regret of a decaying et-greedy heuristic …

Persistent link: https://www.econbiz.de/10012292092

Stable graphical model estimation with Random Forests for discrete, continuous, and mixed variables

Fellinghauer, Bernd; Bühlmann, Peter; Ryffel, Martin; … - In: Computational Statistics & Data Analysis 64 (2013) C, pp. 132-152

Random Forests in combination with Stability Selection allow to estimate stable conditional independence graphs with an error control mechanism for false positive selection. This approach is applicable to graphs containing both continuous and discrete variables at the same time. Its performance...

Persistent link: https://www.econbiz.de/10011056520

Biological age and predicting future health care utilisation

Davillas, Apostolos; Jones, Andrew M. - 2024

collected 5-12 years from baseline. Using least absolute shrinkage and selection operator (LASSO) regression analyses and …

Persistent link: https://www.econbiz.de/10015124940

A Hodrick-Prescott filter with automatically selected jumps

Maranzano, Paolo; Pelagatti, Matteo - 2024

The Hodrick-Prescott filter is a popular tool in macroeconomics for decomposing a time series into a smooth trend and a business cycle component. The last few years have witnessed global events, such as the Global Financial Crisis, the COVID-19 pandemic, and the war in Ukraine, that have had...

Persistent link: https://www.econbiz.de/10014581212

Arellano-Bond lasso estimator for dynamic linear panel models

Chernozhukov, Victor; Fernández-Val, Iván; Huang, Chen; … - 2024

most informative moment conditions, motivating the following approach to remove the bias: First, apply LASSO to the cross …

Persistent link: https://www.econbiz.de/10014581834

Biological Age and Predicting Future Health Care Utilisation

Davillas, Apostolos; Jones, Andrew M. - 2024

collected 5-12 years from baseline. Using least absolute shrinkage and selection operator (LASSO) regression analyses and …

Persistent link: https://www.econbiz.de/10015061906

Fused LASSO as Non-crossing Quantile Regression

Szendrei, Tibor; Bhattacharjee, Arnab; Schaffer, Mark E - 2024

Quantile crossing has been a challenge for quantile regression, leading to research in how to obtain monotonically increasing quantile estimates. While important contributions, these papers do not provide insight into how enforcing monotonicity influences the estimated coefficients. This paper...

Persistent link: https://www.econbiz.de/10015061935