Traditional lending relies on collateral and a financial history that productive smallholder farmers may find difficult to ...

Curious about how to secure renewable-dominant power systems? A team from Shandong University developed a method combining GBDT and FP-Growth algorithms. It quickly assesses cascading failure risks, ...

Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs.

Abstract: We propose a soft gradient boosting framework for sequential regression that embeds a learnable linear feature transform within the boosting procedure. At each boosting iteration, we train a ...

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

The new Instagram feature reveals what the algorithm thinks you like and lets you adjust it, reshaping how content gets recommended on Reels. Instagram launched Your Algorithm in the U.S. today, a ...