UC Santa Barbara computer scientist Daniel Lokshtanov is advancing fundamental understanding of computational efficiency through groundbreaking research on quasi-polynomial time algorithms, supported ...

Daniel Lokshtanov’s work explores the limits of what computers can solve, paving the way for advances in artificial intelligence and computational efficiency.

Researchers from Google Quantum AI report that their quantum processor, Willow, ran an algorithm for a quantum computer that ...

From creating personalized recommendations to enabling complex machine learning systems, this algorithm is behind much of ...

Google scientists say they have taken a major step toward solving one of the hardest problems in computing. Their latest experiment, they argue, provides the most ...

Like humans, artificial intelligence learns by trial and error, but traditionally, it requires humans to set the ball rolling ...

Abstract: A signal processing method combining adaptive Singular Spectrum Decomposition (SSD) with Transient Extracting Transform (TET) is proposed to address the challenge of weak energy in early ...

The new program is validated in a set of clinical pedigrees demonstrating its practical accuracy and relevance to the field. Collectively, the data are compelling and support the major conclusions of ...

Algorithmic trading is a rule-based system where humans set the parameters in advance. It merges automation with human ...

AI improves renewable energy forecasting accuracy by up to 33%, helping grid operators better integrate solar and wind resources. Predictive maintenance powered by AI reduces equipment downtime by ...

An Iterative Reconstruction Algorithm Based on Detail Transfer for Few-View Computed Tomography. Journal of Signal and ...