Abstract: Tabular data is the most widely used data form in real-world applications, and tree-based models are suitable for it due to their model structures. In practice, it is crucial to quantify ...

Toshiba Corporation has developed a breakthrough algorithm that dramatically boosts the performance of the Simulated Bifurcation Machine (SBM), its proprietary quantum‑inspired combinatorial ...

Meta quietly reorganized its recommendations team last fall to form an elite AI research lab. Yang Song, a former TikTok executive, heads the unit. The crucial Meta division has been adding top talent ...

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 ...

Predicting Parkinson's disease (PD) motor progression remains challenging despite advances in neuroimaging. Blood-based transcriptomic profiling offers a more accessible and cost-effective alternative ...

Recently, a research team led by Prof. ZHAO Bangchuan from the Institute of Solid State Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, in collaboration with Prof. XIAO Yao ...

Cervical intraepithelial neoplasia (CIN) is a group of precancerous lesions associated with invasive carcinoma of the cervix that reflects the continuous progression of cervical cancer (CC). Therefore ...

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 ...

Researchers at Central South University in China have developed a new model to improve ultra-short-term photovoltaic (PV) power prediction, as detailed in their publication in Frontiers in Energy. In ...