This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...
The intersection of evolutionary algorithms and data-driven optimisation is reshaping materials science by offering novel computational frameworks for designing and refining materials. Drawing ...
Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials ...
Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...
BEAVERTON, Ore.--(BUSINESS WIRE)--Gurobi Optimization, LLC, the leader in decision intelligence technology, today released its 2023 State of Mathematical Optimization in Data Science report. The ...
The massive datasets that power machine learning algorithms and systems are complex, noisy, and vulnerable to various kinds of errors, contamination, and adversarial corruptions. As data science and ...
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