Their work demonstrates that quantum circuits for data encoding in quantum machine learning can be greatly simplified without compromising accuracy or robustness. The research was published Sept ...

By 2030, it’s expected that the market for streaming data will eclipse $73 billion, growing nearly 20% each year until then. More impressively, the machine learning market—which brought in $15 ...

EMBL-EBI scientists and collaborators at Heidelberg University have developed CORNETO, a new computational tool that uses ...

Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using ...

Meeting The Data Needs Of AI The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic ...

MIT researchers designed a computationally efficient algorithm for machine learning with symmetric data that also requires fewer data for training than conventional approaches. Their work could inform ...

Her project, “From Dirty Data to Fair Prediction: Data Preparation Framework for End-to-End Equitable Machine Learning,” targets the data-preparation pipeline as a strategic opportunity for ...

One of the key obstacles to efficient quantum machine learning has been encoding classical data into quantum states, a computationally challenging task requiring deeply entangled circuits. To ...