Nonconvex-nonconcave minimax problems have found numerous applications in various fields including machine learning. However, questions remain about what is a good surrogate for local minimax optimum and how to characterize the minimax optimality. Re...
As the complexity of machine learning (ML) models increases and their application in different (and critical) domains grows, there is a strong demand for more interpretable and trustworthy ML. A direct, model-agnostic, way to interpret such models is...
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However, they manage to establish a shaky truce, as both Jackie and Isabel come to terms with the fact that Isabel will soon step into the role of surrogate mother.
I am not the Original Poster. OOP is u/4dagoodtimes and they posted on r/AITAH   # Do NOT comment on Original Posts. See rule 7. This sub has a 7-day waiting period so the latest update is ...
Single-neutron transfer reactions populating states in the continuum are interesting both for structure and astrophysics. In their description often global optical potentials are used for the nucleon-target interactions, and these interactions are ty...
However, they manage to establish a shaky truce, as both Jackie and Isabel come to terms with the fact that Isabel will soon step into the role of surrogate mother.
Jul 26, 2010 · Biden allowed his campaign to be run by surrogates while he remained sheltered in his Delaware basement. Occasionally, he ventured into public but these interactions were tightly …
Correcting measurements for detector effects and constructing appropriate public data representations is a pressing problem in LHC physics. Current methods solve this inverse problem by relying on iterations, minimax optimization, or a surrogate forw...
In this paper, we introduce a new heuristics for global optimization in scenarios where extensive evaluations of the cost function are expensive, inaccessible, or even prohibitive. The method, which we call Landscape-Sketch-and-Step (LSS), combines M...
When using Fe as a surrogate for ``metallicity'', the metallicity is best represented by the dominant species of Fe. Accordingly, we have derived a new globular cluster metallicity scale based on the equivalent widths of FeII lines measured from hi...
Kernel based approximation offers versatile tools for high-dimensional approximation, which can especially be leveraged for surrogate modeling. For this purpose, both "knot insertion" and "knot removal" approaches aim at choosing a suitable subset of...
Digital twins (DTs) are increasingly utilized to monitor, manage, and optimize complex systems across various domains, including civil engineering. A core requirement for an effective DT is to act as a fast, accurate, and maintainable surrogate of it...
Global wildfire models play a crucial role in anticipating and responding to changing wildfire regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire emissions and area burnt on a global scale. However, because of the high d...
Operator learning has emerged as a powerful tool in scientific computing for approximating mappings between infinite-dimensional function spaces. A primary application of operator learning is the development of surrogate models for the solution opera...
[Source. Below I bypassed the pay wall so you can read it.](https://www.telegraph.co.uk/world-news/2023/02/03/medics-apologise-suggesting-brain-dead-women-could-used-surrogate/?fbclid=IwY2xjawHfjLVleH...
The performance of deep neural networks crucially depends on good hyperparameter configurations. Bayesian optimization is a powerful framework for optimizing the hyperparameters of DNNs. These methods need sufficient evaluation data to approximate an...
We provide a unifying approximate dynamic programming framework that applies to a broad variety of problems involving sequential estimation. We consider first the construction of surrogate cost functions for the purposes of optimization, and we focus...
Jul 26, 2010 · Biden allowed his campaign to be run by surrogates while he remained sheltered in his Delaware basement. Occasionally, he ventured into public but these interactions were tightly …
Within integrated tokamak plasma modelling, turbulent transport codes are typically the computational bottleneck limiting their routine use outside of post-discharge analysis. Neural network (NN) surrogates have been used to accelerate these calculat...