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Frameworks and results in distributionally robust optimization
H Rahimian, S Mehrotra - Open Journal of Mathematical Optimization, 2022 - numdam.org
The concepts of risk aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. The statistical learning community has …
have developed significantly over the last decade. The statistical learning community has …
A survey and taxonomy of loss functions in machine learning
L Ciampiconi, A Elwood, M Leonardi… - ar** a framework, along with specific methods, for using data to …
Stochastic first-and zeroth-order methods for nonconvex stochastic programming
In this paper, we introduce a new stochastic approximation type algorithm, namely, the
randomized stochastic gradient (RSG) method, for solving an important class of nonlinear …
randomized stochastic gradient (RSG) method, for solving an important class of nonlinear …
Tfg: Unified training-free guidance for diffusion models
Given an unconditional diffusion model and a predictor for a target property of interest (eg, a
classifier), the goal of training-free guidance is to generate samples with desirable target …
classifier), the goal of training-free guidance is to generate samples with desirable target …