1 citations · 1 across the 2 of their papers we have counts for
5 papers
Optimizing Optimizers: Regret-optimal gradient descent algorithms
Philippe Casgrain, Anastasis Kratsios
The need for fast and robust optimization algorithms are of critical importance in all areas of machine learning. This paper treats the task of designing optimization algorithms as…
Non-Euclidean Universal Approximation
Anastasis Kratsios, Eugene Bilokopytov
Modifications to a neural network's input and output layers are often required to accommodate the specificities of most practical learning tasks. However, the impact of such change…
Partial Uncertainty and Applications to Risk-Averse Valuation
Anastasis Kratsios
This paper introduces an intermediary between conditional expectation and conditional sublinear expectation, called R-conditioning. The R-conditioning of a random-vector in i…
The Universal Approximation Property
Anastasis Kratsios
The universal approximation property of various machine learning models is currently only understood on a case-by-case basis, limiting the rapid development of new theoretically ju…
Optimal Stochastic Decensoring and Applications to Calibration of Market Models
Anastasis Kratsios
Typically flat filling, linear or polynomial interpolation methods to generate missing historical data. We introduce a novel optimal method for recreating data generated by a diffu…