A method for designing neural networks optimally suited for certain tasks
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where confidence in the results of a data analysis might break down.
Keynote speaker Bror Saxberg SM ’85, PhD ’89 encourages understanding learners and their contexts.
Assistant professor of nuclear science and engineering Haruko Wainwright believes environmental monitoring can empower citizens to make informed decisions about their energy and environment.
New LiGO technique accelerates training of large machine-learning models, reducing the monetary and environmental cost of developing AI applications.
Careful planning of charging station placement could lessen or eliminate the need for new power plants, a new study shows.
Researchers used machine learning to build faster and more efficient hash functions, which are a key component of databases.
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.
The Advanced Computing Users Survey, sampling sentiments from 120 top-tier universities, national labs, federal agencies, and private firms, finds the decline in America’s advanced computing lead spans many areas.
The chip, which can decipher any encoded signal, could enable lower-cost devices that perform better while requiring less hardware.
Analyses show stakeholders of all levels must get involved in decarbonizing pavements to reach climate goals.
The receiver chip efficiently blocks signal interference that slows device performance and drains batteries.
A wireless technique enables a super-cold quantum computer to send and receive data without generating too much error-causing heat.
The MicroMasters Program in Statistics and Data Science, with over 1,000 credential holders, brings MIT excellence to learners around the world.
The method enables a model to determine its confidence in a prediction, while using no additional data and far fewer computing resources than other methods.