Machine learning methodologies encompass algorithmic frameworks and architectures for training, optimizing, and deploying models such as neural networks, transformers, diffusion models, and reinforcement learning agents. Work in this area develops new training objectives, curriculum schemes, speculative and efficient decoding, pruning and communication-reduction strategies, and biologically inspired or physics-informed architectures. The domain also includes safety preservation, unlearning, scaling laws, and specialized methods for vision, language, control, and scientific computing, aiming to improve performance, efficiency, robustness, and controllability of complex AI systems.
Machine learning & AI
A new study from the University at Albany shows that artificial intelligence systems may organize information in far more intricate ways than previously thought. The study, "Exploring the Stratified Space Structure of an ...
Jan 31, 2026
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Machine learning & AI
Achieving high reliability in AI systems—such as autonomous vehicles that stay on course even in snowstorms or medical AI that can diagnose cancer from low-resolution images—depends heavily on model robustness. While data ...
Jan 29, 2026
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Machine learning & AI
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective at capturing relationships ...
Jan 28, 2026
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Computer Sciences
How inconvenient would it be if you had to manually transfer every contact and photo from scratch every time you switched to a new smartphone? Current artificial intelligence (AI) models face a similar predicament. Whenever ...
Jan 27, 2026
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Computer Sciences
While popular AI models such as ChatGPT are trained on language or photographs, new models created by researchers from the Polymathic AI collaboration are trained using real scientific datasets. The models are already using ...
Jan 27, 2026
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Security
Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in image-related tasks. These systems have found applications in medical diagnosis, automated data processing, ...
Jan 23, 2026
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Energy & Green Tech
What if traffic could compute? This may sound strange, but researchers at Tohoku University's WPI-AIMR have unveiled a bold new idea: using road traffic itself as a computer.
Jan 22, 2026
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Computer Sciences
A study led by UC Riverside researchers offers a practical fix to one of artificial intelligence's toughest challenges by enabling AI systems to reason more like humans—without requiring new training data beyond test questions.
Jan 22, 2026
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Hardware
In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, slashing energy use by ...
Security
A new forensic framework designed specifically for the Internet of Things (IoT) is discussed in the International Journal of Electronic Security and Digital Forensics. This deep learning-driven system offers benefits over ...
Jan 15, 2026
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