Výsledky vyhledávání - "Sokolov, Vadim O."

Report

Eco-Mobility-on-Demand Fleet Control with Ride-Sharing

Autor: Huang, Xianan, Li, Boqi, Peng, Huei, Auld, Joshua A., Sokolov, Vadim O.

Shared Mobility-on-Demand using automated vehicles can reduce energy consumption and cost for future mobility. However, its full potential in energy saving has not been fully explored. An algorithm to minimize fleet fuel consumption while satisfying

Externí odkaz: http://arxiv.org/abs/1908.09828

Zobrazit plný text záznamu

Report

Data Augmentation for Bayesian Deep Learning

Autor: Wang, Yuexi, Polson, Nicholas G., Sokolov, Vadim O.

Deep Learning (DL) methods have emerged as one of the most powerful tools for functional approximation and prediction. While the representation properties of DL have been well studied, uncertainty quantification remains challenging and largely unexpl

Externí odkaz: http://arxiv.org/abs/1903.09668

Zobrazit plný text záznamu

Report

Deep Learning

Autor: Polson, Nicholas G., Sokolov, Vadim O.

Deep learning (DL) is a high dimensional data reduction technique for constructing high-dimensional predictors in input-output models. DL is a form of machine learning that uses hierarchical layers of latent features. In this article, we review the s

Externí odkaz: http://arxiv.org/abs/1807.07987

Zobrazit plný text záznamu

Report

Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading

Autor: Dixon, Matthew F., Polson, Nicholas G., Sokolov, Vadim O.

Deep learning applies hierarchical layers of hidden variables to construct nonlinear high dimensional predictors. Our goal is to develop and train deep learning architectures for spatio-temporal modeling. Training a deep architecture is achieved by s

Externí odkaz: http://arxiv.org/abs/1705.09851

Zobrazit plný text záznamu