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pro vyhledávání: '"Machlanski, Damian"'
Arguably, for the latter part of the late 20th and early 21st centuries, games have been seen as the drosophila of AI. Games are a set of exciting testbeds, whose solutions (in terms of identifying optimal players) would lead to machines that would p
Externí odkaz:
http://arxiv.org/abs/2406.18178
Hyperparameters play a critical role in machine learning. Hyperparameter tuning can make the difference between state-of-the-art and poor prediction performance for any algorithm, but it is particularly challenging for structure learning due to its u
Externí odkaz:
http://arxiv.org/abs/2310.18212
The performance of most causal effect estimators relies on accurate predictions of high-dimensional non-linear functions of the observed data. The remarkable flexibility of modern Machine Learning (ML) methods is perfectly suited to this task. Howeve
Externí odkaz:
http://arxiv.org/abs/2303.01412
Publikováno v:
IEEE Access, vol. 12, pp. 38562-38574, 2024
Inferring individualised treatment effects from observational data can unlock the potential for targeted interventions. It is, however, hard to infer these effects from observational data. One major problem that can arise is covariate shift where the
Externí odkaz:
http://arxiv.org/abs/2203.08570
Akademický článek
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