Abstract: Neural networks that overlook the underlying causal relationships among observed variables pose significant risks in high-stakes decision-making contexts due to concerns about the robustness ...
A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...
Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...
Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...
In recent years, something unexpected has been happening in artificial intelligence. Modern AI appears to be breaking a rule that statisticians have preached for nearly a century: Keep models in a ...
This repository provides implementation for SNBO (Scalable Neural Network-based Blackbox Optimization) — a novel method for efficient blackbox optimization using neural networks. It also includes code ...
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