Abstract: Solving constrained multi-objective optimization problems (CMOPs) is a challenging task due to the presence of multiple conflicting objectives and intricate constraints. In order to better ...
The team's automated reasoning research aims to build algorithms that allow computers to perform logical reasoning. The output of these algorithms is traditionally binary: satisfiable or unsatisfiable ...
A new academic study argues that the structural reliance of artificial intelligence (AI) systems on classification models creates significant challenges when AI systems attempt to represent fluid and ...
Read more about AI and machine learning drive digital transformation across global mining operations on Devdiscourse ...
Abstract: The challenge of imbalanced data classification stems from the uneven distribution of data across classes, which is a formidable obstacle for traditional classifiers. Although numerous ...
Choosing a Tinder profile picture may feel like a free, personal and creative act. But how true is that? A new study from the Universitat Oberta de Catalunya (UOC) shows that, far from being unique, ...
Sasha S. Rao and Todd M. Hopfinger of Sterne, Kessler, Goldstein & Fox PLLC discuss challenges in meeting patent law's disclosure requirements for inventions involving artificial intelligence, ...
Objectives To evaluate whether type 2 diabetes mellitus (T2DM) presence and severity are associated with differences in global and domain-specific cognitive function among US adults, using ...
We use Quarto to generate all outputs. @book{Nguyen2025TLBoAlg, author = {Duc-Tam Nguyen}, title = {The Little Book of algorithms}, year = {2025}, url = {https ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results