Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
Abstract: The problem of designing adaptive stepsize sequences for the gradient descent method applied to convex and locally smooth functions is studied. We take an adaptive control perspective and ...
Abstract: In this work, we revisit a classical distributed gradient-descent algorithm, introducing an interesting class of perturbed multi-agent systems. The state of each subsystem represents a local ...
The core challenge in application of the ANN framework is selecting appropriate hyperparameters. The gradient descent algorithm is commonly used to optimize these hyperparameters by moving them in the ...
If you need support for a new econometric algorithm or have an idea for an implementation, please submit your request via GitHub Issues. After evaluation, we'll add it to our DEVPLAN for future ...
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