3Q: David Simchi-Levi on advancing global retail operations through analytics and machine learning
David Simchi-Levi discusses insights from recent research in collaboration with some of the world's largest retailers.
David Simchi-Levi discusses insights from recent research in collaboration with some of the world's largest retailers.
Advances in computer vision inspired by human physiological and anatomical constraints are improving pattern completion in machines.
Model extracts granular behavioral patterns from transaction data to more accurately flag suspicious activity.
Model learns to pick out objects within an image, using spoken descriptions.
A key part of the MIT Quest for Intelligence, J-Clinic builds on MIT expertise across multiple scientific disciplines.
Chemical engineering graduate student was named a “machine-learning maestro” by the magazine.
Model from MIT Lincoln Laboratory Intelligence and Decision Technologies Group sets a new standard for understanding how a neural network makes decisions.
Adaptable Interpretable Machine Learning project is redesigning machine learning models so humans can understand what computers are thinking.
Neural network learns speech patterns that predict depression in clinical interviews.
By training on patients grouped by health status, neural network can better estimate if patients will die in the hospital.
The dynamic programming language, which is free and open source, combines the speed and popular features of the best scientific and technical software.
Novel combination of two encryption techniques protects private data, while keeping neural networks running quickly.
Machine-learning system determines the fewest, smallest doses that could still shrink brain tumors.
FinTech@CSAIL industry collaboration will work to improve business models, access to data, and security in the finance sector.
Personalized machine-learning models capture subtle variations in facial expressions to better gauge how we feel.