Researchers provide new insights into human cognition by prioritizing interpretability in predictive modeling of intelligence ...
In short, training builds the foundation, while inferencing brings that knowledge to life in practical, real-world ...
A machine learning (ML) model incorporating both clinical and genomic factors ... to inform second-line treatment options and clinical trials. This could put us one step closer to staying ahead of ...
Researchers developed an AI debiasing technique that improves the fairness of a machine-learning model by boosting its performance for subgroups that are underrepresented in its training data, while ...
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Identifying and Mitigating Bias in Machine Learning ModelsA new MIT technique improves machine learning by removing key biased data points, boosting model performance for minority ...
Researchers in the Department of Mechanical Engineering have developed a novel machine learning model combining graph neural ...
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Improving the Interpretability of Machine Learning ModelsThe EXPLINGO system by MIT converts intricate machine-learning explanations into readable narratives, improving trust in AI ...
Researchers developed a system that converts AI explanations into narrative text that can be more easily understood by users. This system could help people determine when to trust a model's ...
Models can be deployed offline or online at the edge to drive execution of real-time actions. Actions can vary from early ...
University of Michigan researchers showed how mechanical neural networks-the black lattices of triangles-could be trained to solve problems. Image ...
University of Michigan physicists have devised an algorithm that provides a mathematical framework for how learning works in ...
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