Abstract: Dynamic environments pose great challenges for expensive optimization problems, as the objective functions of these problems change over time and thus require remarkable computational ...

We've wondered for centuries whether knowledge is latent and innate or learned and grasped through experience, and a new research project is asking the same question about AI. When you purchase ...

where the output is not from a fixed vocabulary, but a sequence of pointers to elements from the input. Main idea: Instead of producing an output token from a fixed-size vocabulary, the model points ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

Annealing processors (APs) are gaining popularity for solving complex optimization problems. Fully-coupled Ising model APs are especially valued for their flexibility, but balancing capacity (number ...

Python and MATLAB are valuable for an electrical engineer's career, but the better choice depends on your field, industry, and career goals. Electrical engineers face many challenges: dealing with ...

Research paper by Bjørnar Luteberget and Giorgio Sartor wins 2024 FICO® Xpress Best Paper Award; the algorithm is now in FICO® Xpress Solver “When solving a very large computational problem, ...