1 citations · 1 across the 5 of their papers we have counts for
5 papers
Corrected Forecast Combinations
Chu-An Liu, Andrey L. Vasnev
This paper proposes corrected forecast combinations when the original combined forecast errors are serially dependent. Motivated by the classic Bates and Granger (1969) example, we…
Generalized Laplacian Regularized Framelet Graph Neural Networks
Zhiqi Shao, Andi Han, Dai Shi +2
This paper introduces a novel Framelet Graph approach based on p-Laplacian GNN. The proposed two models, named p-Laplacian undecimated framelet graph convolution (pL-UFG) and gener…
Flexible global forecast combinations
Ryan Thompson, Yilin Qian, Andrey L. Vasnev
Forecast combination -- the aggregation of individual forecasts from multiple experts or models -- is a proven approach to economic forecasting. To date, research on economic forec…
Regularized Flexible Activation Function Combinations for Deep Neural Networks
Renlong Jie, Junbin Gao, Andrey Vasnev +1
Activation in deep neural networks is fundamental to achieving non-linear mappings. Traditional studies mainly focus on finding fixed activations for a particular set of learning t…
Adaptive Hierarchical Hyper-gradient Descent
Renlong Jie, Junbin Gao, Andrey Vasnev +1
In this study, we investigate learning rate adaption at different levels based on the hyper-gradient descent framework and propose a method that adaptively learns the optimizer par…