Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

Forecasting, a fundamental task in machine learning, involves predicting future values of a time series based on its historical behavior. This paper introduces a novel Hierarchical Patch Based ...

1 School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou, China. 2 School of Science and Technology, Hunan University of Technology, Zhuzhou, China. To address the multicoupling ...

Research Laboratory in Bionanomaterials, LPbio, Department of Chemistry, Federal University of Viçosa, 36570-900 Viçosa, Minas Gerais, Brazil ...

Introduction: We present Quantum Adaptive Search (QAGS), a hybrid quantum-classical algorithm for global optimization of multivariate functions. The method employs an adaptive mechanism that ...

Implementation of numerical optimization algorithms in MATLAB, including derivative-free and gradient-based methods for unconstrained problems, and projection techniques for constrained optimization.

Abstract: Online advertising is typically implemented via real-time bidding, and advertising campaigns are then defined as extremely high-dimensional optimization problems. To solve these problems in ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

Palo Alto, California-based D-Wave Quantum Inc. claims to be the first company that sells computers that leverage quantum effects in their operation. The company recently demonstrated how its quantum ...

Heidi S. Enger ’27, an Associate Editorial Editor, is a Social Studies Concentrator in Eliot House. She’s enrolled in Ec10b this semester (don’t ask). Harvard students have to stop treating life like ...