Deep hedging is a deep-learning-based framework for derivative hedging i...
Machine learning is an increasingly popular tool with some success in
pr...
This paper provides a unified perspective for the Kullback-Leibler
(KL)-...
In contrastive representation learning, data representation is trained s...
The main task we consider is portfolio construction in a speculative mar...
Investors try to predict returns of financial assets to make successful
...
Recent developments in deep learning techniques have motivated intensive...
We formalize an equivalence between two popular methods for Bayesian
inf...
Generative adversarial networks, or GANs, commonly display unstable beha...
We study the problem of estimating piecewise monotone vectors. This prob...