Biologically plausible learning now reaches 96.7% on MNIST and 61.7% on CIFAR-10 without backpropagation, as Sakana AI ...

Adding experience level agreements to an outsourcing contract isn’t as simple as it sounds, but successful programs start ...

Memristor-based chips could solve demanding optimization problems far faster and with less energy by replacing dense ...

This type of problem – known as a combinatorial optimization problem – lies at the heart of many challenges in science, technology, and business. A new German-Taiwanese research project involving TU ...

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...

Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

Optimization problems as a research area encompass the theoretical and algorithmic study of selecting the best solution from a feasible set according to one or more objective functions, under possibly ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...

This study presents an optimization method for arranging lattice radiotherapy (LRT) targets to enhance the contrast between peak and valley doses, aiming to improve the treatment effectiveness and ...

Assignment problems lie at the heart of combinatorial optimisation, seeking the most efficient mapping of a set of agents to a set of tasks under cost or profit criteria. The classical linear ...