20 citations · 24 across the 6 of their papers we have counts for
7 papers
LegendreTron: Uprising Proper Multiclass Loss Learning
Kevin Lam, Christian Walder, Spiridon Penev +1
Loss functions serve as the foundation of supervised learning and are often chosen prior to model development. To avoid potentially ad hoc choices of losses, statistical decision t…
Hellinger-Bhattacharyya cross-validation for shape-preserving multivariate wavelet thresholding
Carlos Aya-Moreno, Gery Geenens, Spiridon Penev
The benefits of the wavelet approach for density estimation are well established in the literature, especially when the density to estimate is irregular or heterogeneous in smoothn…
Stability and Sample-based Approximations of Composite Stochastic Optimization Problems
Darinka Dentcheva, Yang Lin, Spiridon Penev
Optimization under uncertainty and risk is indispensable in many practical situations. Our paper addresses stability of optimization problems using composite risk functionals which…
The impact of model risk on dynamic portfolio selection under multi-period mean-standard-deviation criterion
Spiridon Penev, Pavel V. Shevchenko, Wei Wu
We quantify model risk of a financial portfolio whereby a multi-period mean-standard-deviation criterion is used as a selection criterion. In this work, model risk is defined as th…
Shape-preserving wavelet-based multivariate density estimation
Carlos Aya Moreno, Gery Geenens, Spiridon Penev
Wavelet estimators for a probability density f enjoy many good properties, however they are not "shape-preserving" in the sense that the final estimate may not be non-negative or i…
Statistical Estimation of Composite Risk Functionals and Risk Optimization Problems
Darinka Dentcheva, Spiridon Penev, Andrzej Ruszczynski
We address the statistical estimation of composite functionals which may be nonlinear in the probability measure. Our study is motivated by the need to estimate coherent measures o…