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2. Generalization error - Wikipedia

   en.wikipedia.org/wiki/Generalization_error

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3. Apple says it will fix software problems blamed for making ...

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   Apple is blaming a software bug and other issues tied to popular apps such as Instagram and Uber for causing its recently released iPhone 15 models to heat up and spark complaints about becoming ...

4. Error-driven learning - Wikipedia

   en.wikipedia.org/wiki/Error-driven_learning

   NER is the task of identifying and classifying entities (such as persons, locations, organizations, etc.) in a text. Error-driven learning can help the model learn from its false positives and false negatives and improve its recall and precision on (NER). [5] In the context of error-driven learning, the significance of NER is quite profound.

5. Weak supervision - Wikipedia

   en.wikipedia.org/wiki/Weak_supervision

   Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the advent of large language models due to large amount of data required to train them.

6. Bias–variance tradeoff - Wikipedia

   en.wikipedia.org/wiki/Bias–variance_tradeoff

   The bias–variance decomposition forms the conceptual basis for regression regularization methods such as LASSO and ridge regression.Regularization methods introduce bias into the regression solution that can reduce variance considerably relative to the ordinary least squares (OLS) solution.

7. Account Management - AOL Help

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   If you use a 3rd-party email app to access your AOL Mail account, you may need a special code to give that app permission to access your AOL account. Learn how to create and delete app passwords. Account Management · Apr 17, 2024

8. Reinforcement learning from human feedback - Wikipedia

   en.wikipedia.org/wiki/Reinforcement_learning...

   RLHF suffers from challenges with collecting human feedback, learning a reward model, and optimizing the policy. [38] Compared to data collection for techniques like unsupervised or self-supervised learning, collecting data for RLHF is less scalable and more expensive. Its quality and consistency may vary depending on the task, interface, and ...

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