Abstract: For distributed-drive electric vehicles, torque vectoring control based on model predictive control (MPC) has emerged as a preferred strategy to achieve superior performance across diverse ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...

I've been working with the code and noticed that the current model (RandomForestRegressor) could benefit from hyperparameter tuning. The current setup uses default parameters, which may not be optimal ...

Functions are the building blocks of Python programming. They let you organize your code, reduce repetition, and make your programs more readable and reusable. Whether you’re writing small scripts or ...

Functions are the building blocks of Python programs. They let you write reusable code, reduce duplication, and make projects easier to maintain. In this guide, we’ll walk through all the ways you can ...

Supervised Fine-Tuning (SFT) is a standard technique for adapting LLMs to new tasks by training them on expert demonstration datasets. It is valued for its simplicity and ability to develop ...

Here: https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/tuner.py#L1655 in case of framework estimator, the CategoricalParameter is encoded using ...

The title of this article was erroneously given as: Paired competing neurons improving STDP supervised local learning in Spiking Neural Networks. The correct title of the article is: Paired competing ...

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