A bill moving through the California Legislature would test students as early as kindergarten on math. It's part of an effort ...

Abstract: Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on ...

Also available: the recorded lectures from the 2021 course instance (most in Swedish, some in English). This repository is mainly the home of the DSLsofMath book (originating from the course lecture ...

Math AI tools use advanced algorithms to instantly recognize equations, generate accurate solutions, and explain each step clearly for better understanding. Beyond providing answers, these tools help ...

Abstract: Several problems in signal processing have been formulated in terms of the Canonical Polyadic Decomposition of a higher-order tensor with one or more Vandermonde constrained factor matrices.

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The Langlands program has inspired and befuddled mathematicians for more than 50 years. A major advance has now opened up new worlds for them to explore One of the biggest stories in science has been ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

Computer scientists are a demanding bunch. For them, it’s not enough to get the right answer to a problem — the goal, almost always, is to get the answer as efficiently as possible. Take the act of ...

Developing faster algorithms is an important but elusive goal for data scientists. The ability to accelerate complex computing tasks and reduce latency has far-reaching ramifications in areas such as ...