Tech Xplore on MSN
Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Federated learning makes it possible for agency employees to collaborate on advanced artificial intelligence models without compromising data control or operational security. The process serves as a ...
Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...
Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...
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