The big challenge in deep learning is that you need a lot of data to train the neural network. Fortunately, one of my ...

NTT Research, Inc. and NTT R&D, divisions of NTT , announced that their scientists will present nine papers at the International Conference on Learning Representations (ICLR) 2025 ...

A new communication-collective system, OptiReduce, speeds up AI and machine learning training across multiple cloud servers by setting time boundaries rather than waiting for every server to catch up, ...

as well as how they inform the ways that neural networks learn from data, is crucial for improving the interpretability, efficiency, and generalizability of deep learning models. With that mind ...

The Hacker News is the top cybersecurity news platform, delivering real-time updates, threat intelligence, data breach ...

One notable missing feature in most ANN models is top-down feedback, i.e. projections from higher-order layers to lower-order layers in the network. Top-down feedback is ubiquitous in the brain, and ...

View software available in the Integrated Systems Biology and AI — Tailored Pharmacology and Precision Medicine Lab led by Hu ...

Performance Metrics of the Model: The effectiveness of AI-based hardware Trojan (HT) detection models can be assessed by a range of classification metrics, including accuracy, precision, recall (true ...

A new scientific machine learning framework developed by Professors Horacio D. Espinosa, Sridhar Krishnaswamy, and ...

Data sharing becomes more challenging when AI and multi-die assemblies are involved.