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Found 4 papers, 1 papers with code
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.
A Fine-Grained Variant of the Hierarchy of Lasserre
There has been much recent interest in hierarchies of progressively stronger convexifications of polynomial optimisation problems (POP).
Data-driven Distributionally Robust Polynomial Optimization
We consider robust optimization for polynomial optimization problems where the uncertainty set is a set of candidate probability density functions.
Mean squared error minimization for inverse moment problems
We consider the problem of approximating the unknown density $u\in L^2(\Omega,\lambda)$ of a measure $\mu$ on $\Omega\subset\R^n$, absolutely continuous with respect to some given reference measure $\lambda$, from the only knowledge of finitely many moments of $\mu$.
Optimization and Control
