The cybersecurity market is undergoing rapid expansion, propelled by an escalating wave of cyber threats that challenge organizations globally. As digital transformation reshapes business operations ...

Industrial AI deployment traditionally requires onsite ML specialists and custom models per location. Five strategies ...

ARTDAI, a fine art and collectibles market data and analytics company, today announced the launch of ArtExpert 3.0 ("AE3"), an AI-native data processing platform that will be integrated across ...

Understand Local Response Normalization (LRN) in deep learning: what it is, why it was introduced, and how it works in convolutional neural networks. This tutorial explains the intuition, mathematical ...

XRP sentiment hits extreme fear at 24 while institutional ETFs accumulated $424M in December alone, and $1.3 billion in 50 days. Machine learning models achieve 70-91% accuracy predicting crypto moves ...

@InProceedings{pstone_simba, author = {Hojoon Lee and Youngdo Lee and Takuma Seno and Donghu Kim and Peter Stone and Jaegul Choo}, title = {Hyperspherical Normalization for Scalable Deep Reinforcement ...

ABSTRACT: Bipolar disorder is a complex psychiatric condition characterized by high variability in treatment response, posing a major challenge for clinicians striving to personalize care. Traditional ...

Background: High-risk chest pain is a critical presentation in emergency departments, frequently indicative of life-threatening cardiopulmonary conditions. Rapid and accurate diagnosis is pivotal for ...

Background: Poly(ADP)-ribose polymerase inhibitors (PARPi) have brought a significant breakthrough in the maintenance treatment of ovarian cancer. However, beyond BRCA mutation/HRD, the direct impact ...

Abstract: Optimizing machine learning (ML) model performance relies heavily on appropriate data preprocessing techniques. Despite the widespread use of standardization and normalization, empirical ...