Every online bank transfer, private message and Bitcoin transaction rests on the assumption that some math problems are ...

The next frontier in automotive AI is about equipping vehicles to learn, adapt and evolve through orchestrated data that ...

TEL AVIV, Israel, Dec. 10, 2025 (GLOBE NEWSWIRE) -- Israeli start-up LightSolver, inventor of a new laser-based computing paradigm, today announced that Senior Algorithmics Researcher Dr. Dani Gluck ...

TEL AVIV, Israel, Dec. 10, 2025 (GLOBE NEWSWIRE) -- Israeli start-up LightSolver, inventor of a new laser-based computing paradigm, today announced that Senior Algorithmics Researcher Dr. Dani Gluck ...

Some algorithms solve problems. This one changed civilization. From guiding satellites to securing your bank account, its influence reaches every corner of technology. It started with a simple insight ...

This project is my independent research into SAT solvers written entirely in Python, designed to explore the theory and practice of propositional satisfiability. It begins with a baseline DPLL ...

These days, everyone seems to have an opinion about A.I. companions. Last year, I found myself joining the debate, publishing a paper—co-written with two fellow psychology professors and a philosopher ...

MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.

Caption:MIT researchers created a periodic table of machine learning that shows how more than 20 classical algorithms are connected. The new framework sheds light on how scientists could fuse ...

Abstract: Constrained Path-based Testing (CPT) is a technique that extends traditional path-based testing by adding constraints on the order or presence of specific sequences of actions in the tests ...

I'd suggest keeping the current implementation as a fallback, but using a WebAssembly implementation when available. The current solver algorithm is extremely slow; on my computer, a native C ...

Abstract: In federated learning, non-independently and non-identically distributed heterogeneous data on the clients can limit both the convergence speed and model utility of federated learning, and ...