What are the limitations of cross-validation for estimating generalization error, especially in the presence of overfitting?

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Mar 18, 2024 ... The difference is the scale: AI systems are so data-hungry and intransparent that we have even less control over what information about us is ... A recent example highlighting concerns over the use of publicly available information to communicate between firms involves the Alberta wholesale electricity ... (This is joint work with Jerry Zhu, Chuck Dyer, and Jake Rosin in Computer Sciences.) Oct. 30 Michael Titelbaum, Department of Philosophy. Why Bayesianism? Over ... Nov 6, 2020 ... We present an information-theoretic framework for under- standing overfitting and underfitting in machine learning and prove the formal ... Sep 15, 2021 ... Critics noted that patients were not afforded agency over the use of their information, nor were privacy impacts adequately discussed [22]. A ... Nov 5, 2019 ... All of the information criteria effectively transform what would have been comparison of log likelihoods over models into a comparison of ... Nov 12, 2024 ... From our MACD data, we created graphs of the MACD indicator and the corresponding signal line over 26 day periods, which served as our image ... Jul 27, 2024 ... ... informational impact these orders have, varying across stock ... Overfitting, ML, data snooping... And papers writing instead of ... Feb 25, 2015 ... ... over a wide range of ecological conditions. The model explicitly tracks individual animal informational state over space and time, with ... Oct 4, 2011 ... The Informational Content of the Embedded Deflation Option in TIPS * ... We include nominal T-Notes in our analysis to avoid overfitting the ...
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