As post-quantum security moves closer to reality, efforts like Google’s Merkle Tree Certificates highlight the need to ...

Water scarcity is emerging as a major threat in contemporary agriculture, necessitating the development of innovative means ...

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...

Large language models (LLMs) can teach other algorithms unwanted traits, which can persist even when training data has been ...

Scientists at the European Centre for Medium-Range Weather Forecasts have unveiled a machine learning technique that pinpoints optimal locations for tree planting, offering a powerful tool for climate ...

The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the ...

This project implements an automated assignment scheduling system using Monte Carlo Tree Search (MCTS) to optimize classroom allocation for educational courses. The system assigns courses to ...

Abstract: Real-world optimization problems are becoming increasingly complex and require effective and versatile algorithms to provide reliable solutions. However, the no-free-lunch theorem indicates ...

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning ...

Abstract: As an amendment to the deep forest, deep forest regression (DFR) has been recently proposed for industrial process modeling. However, training DFR models is an arduous task in terms of ...