Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Ushiyama, Kansei"'
Autor:
Chikahara, Yoichi, Ushiyama, Kansei
There is a growing interest in estimating heterogeneous treatment effects across individuals using their high-dimensional feature attributes. Achieving high performance in such high-dimensional heterogeneous treatment effect estimation is challenging
Externí odkaz:
http://arxiv.org/abs/2404.17483
We propose a new unified framework for describing and designing gradient-based convex optimization methods from a numerical analysis perspective. There the key is the new concept of weak discrete gradients (weak DGs), which is a generalization of DGs
Externí odkaz:
http://arxiv.org/abs/2302.07404
Some continuous optimization methods can be connected to ordinary differential equations (ODEs) by taking continuous limits, and their convergence rates can be explained by the ODEs. However, since such ODEs can achieve any convergence rate by time s
Externí odkaz:
http://arxiv.org/abs/2206.02599
Publikováno v:
Numerical Algorithms; Jul2024, Vol. 96 Issue 3, p1331-1362, 32p
