Results 21 to 30 of about 90,500 (318)
On the Optimality of Optimal Income Taxation [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Asymptotic optimality in stochastic optimization [PDF]
We study local complexity measures for stochastic convex optimization problems, providing a local minimax theory analogous to that of Hájek and Le Cam for classical statistical problems. We give complementary optimality results, developing fully online methods that adaptively achieve optimal convergence guarantees. Our results provide function-specific
Duchi, John C., Ruan, Feng
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Clarifying the Notion “Parameter”
This article aims to reflect on linguistic architecture by re-examining language variation. Three progressively deeper forms of variation are suggested, each of which arguably contributes to this exercise in rather different ways.
Juan Uriagereka
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Metabolism at Evolutionary Optimal States
Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular ...
Iraes Rabbers +5 more
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Optimizing microservices with hyperparameter optimization
In the last few years, the cloudification of applications requires new concepts and techniques to fully reap the benefits of the new computing paradigm. Among them, the microservices architectural style, which is inspired by service-oriented architectures, has gained attention from both industry and academia.
Hai Dinh-Tuan +2 more
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Social inhibition maintains adaptivity and consensus of honeybees foraging in dynamic environments [PDF]
To effectively forage in natural environments, organisms must adapt to changes in the quality and yield of food sources across multiple timescales. Individuals foraging in groups act based on both their private observations and the opinions of their ...
Subekshya Bidari +2 more
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Optimization and Optimizers for Adversarial Robustness
Empirical robustness evaluation (RE) of deep learning models against adversarial perturbations entails solving nontrivial constrained optimization problems. Existing numerical algorithms that are commonly used to solve them in practice predominantly rely on projected gradient, and mostly handle perturbations modeled by the $\ell_1$, $\ell_2$ and $\ell_\
Hengyue Liang +5 more
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Numerous studies have shown that temperate and boreal forests are limited by nitrogen (N) availability. However, few studies have provided a detailed account of how carbon (C) acquisition of such forests reacts to increasing N supply.
Lasse Tarvainen +4 more
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Optimal Solvers for PDE-Constrained Optimization [PDF]
Optimization problems with constraints which require the solution of a partial differential equation arise widely in many areas of the sciences and engineering, in particular in problems of design. The solution of such PDE-constrained optimization problems is usually a major computational task.
Tyrone Rees +2 more
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9 pages, 4 figures. Accompanying paper of arXiv:2111.12130.
Kamil Korzekwa, Matteo Lostaglio
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