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Multi-block ADMM Heuristics for Mixed-Binary Optimization on Classical and Quantum Computers
Solving combinatorial optimization problems on current noisy quantum devices is currently being advocated for (and restricted to) binary polynomial optimization with equality constraints via quantum heuristic approaches.
Combinatorial Optimization
Quantum Physics
Optimization and Control
On model selection for scalable time series forecasting in transport networks
We discuss that modelling temporal and spatial features into deep learning predictors can be helpful for long-term predictions, while simpler, not deep learning-based predictors, achieve very satisfactory performance for link-based and short-term forecasting.
Optimization Problems for Machine Learning: A Survey
This paper surveys the machine learning literature and presents in an optimization framework several commonly used machine learning approaches.
