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Search · four archives
19 papers · ranked by Valyu relevance
Achim Langenbucher, Nóra Szentmáry, Alan Cayless, Jascha Wendelstein + 2 more
In this context, formula constants were optimised for statistical metrics of the SEQ prediction error PE. For the statistical metrics we used: the sum of squared PE (SoSPE) which minimises the ‘energy’ of the prediction error, the sum of the absolute PE (SoAPE, as typically used in scientific reports on the performance…
Achim Langenbucher, Nóra Szentmáry, Alan Cayless, Jascha Wendelstein + 2 more
In this study for both datasets four situations have been considered for our formula constant optimisation: 1. A standard optimisation of the formula using the keratometer index or corneal refractive index as proposed by the formula authors. The formula constants pACD, SF, a0/a1/a2 and C/H/R were optimised for the…
Achim Langenbucher, Nóra Szentmáry, Jascha Wendelstein, Alan Cayless + 2 more
4.1### Formula constant optimization in general Correct and accurate formula constants are crucial for the performance of IOL power calculations in cataract surgery. However, there are no common standards or guidelines on how to optimize formula constants (Aristodemou et al., ; El-Khayat & Tesha, ; Galvis et al., …
Achim Langenbucher, Jascha Wendelstein, Alan Cayless, Thomas Olsen + 2 more
1## INTRODUCTION Lens power formulae based on vergence calculations with simplification to the paraxial space are widely used to determine the power of intraocular lenses (IOL) prior to cataract surgery. These formulae are designed to be generally valid for all lens designs and materials (Aristodemou et al., …
Ezio Bartocci, Luca Bortolussi, Guido Sanguinetti
We present a novel approach to learn the formulae characterising the emergent behaviour of a dynamical system from system observations. At a high level, the approach starts by devising a statistical dynamical model of the system which optimally fits the observations. We then propose general optimisation strategies for…
Yifan Wu, Aron Walsh, Alex Ganose
What is the minimum number of experiments, or calculations, required to find an optimal solution? Relevant chemical problems range from identifying a compound with target functionality within a given phase space to controlling materials synthesis and device fabrication conditions. A common feature in this application…
Michael R. Tehranchi
In this note, Black–Scholes implied volatility is expressed in terms of various optimisation problems. From these representations, upper and lower bounds are derived which hold uniformly across moneyness and call price. Various symmetries of the Black– Scholes formula are exploited to derive new bounds from old. These…
Namhoon Cho, Hyo‐Sang Shin
This study presents a constructive methodology for designing accelerated convex optimisation algorithms in continuous-time domain. The two key enablers are the classical concept of passivity in control theory and the time-dependent change of variables that maps the output of the internal dynamic system to the…
Ke Ma, Stephan M. Goetz
Transcranial magnetic stimulation (TMS) is a widely-used noninvasive brain stimulation technique through electromagnetic induction. Nowadays commercial TMS devices routinely use conventional biphasic pulses for repetitive TMS protocols and monophasic pulses for single-pulse stimulation. They respectively generate…
Mahdiar Sadeghi, M. Ali Al-Radhawi, Michael Margaliot, Eduardo Sontag
The Ribosome Flow Model (RFM) model is a deterministic model of translation with n sites , It is a mean-field approximation of a standard model for translation elogation Totally Asymmetric Simple Exclusion Process (TASEP) . The model can be written as follows: where x(t) is the occupancy vector x(t) = [x_1_(t)…
Wang Zhi-feng, Li Long-Long, Zeng, Chunyan
Within the current sphere of deep learning research, despite the extensive application of optimization algorithms such as Stochastic Gradient Descent (SGD) and Adaptive Moment Estimation (Adam), there remains a pronounced inadequacy in their capability to address fluctuations in learning efficiency, meet the demands of…
Liwei Cao, Danilo Russo, Vassilios S. Vassiliadis, Alexei Lapkin
A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor…
Kazunori D Yamada
In the deep learning era, a gradient descent method is the most common method to optimize parameters of neural networks. Among various mathematical optimization methods, a gradient descent method is the most naive method. Although controlling a learning rate of the method is necessary for quick convergence, the…
Shannon Bonke, Giovanni Trezza, Luca Bergamasco, Hongwei Song + 4 more
The sunlight-driven reduction of CO2 into fuels and platform chemicals is a promising approach to enable a circular economy. However, established optimisation approaches are poorly suited to multi-variable multi-metric photocatalytic systems because they aim to optimise one performance metric while sacrificing the…
Andrew McCluskey
The use of mathematical transformations to reduce non-linear functions to linear problems, which can be tackled with analytical linear regression, is commonplace in the chemistry curriculum. The linearization procedure, however, assumes an incorrect statistical model for real experimental data; leading to biased…
Dragos-Patru Covei
This study investigates a stochastic production planning problem with regimeswitching parameters, inspired by economic cycles impacting production and inventory costs. The model considers types of goods and employs a Markov chain to capture probabilistic regime transitions, coupled with a multidimensional Brownian…
Kleitos Papadopoulos
In this paper, we study the single-item economic lot-sizing problem with production cost functions that are piecewise linear. The lot-sizing problem stands as a foundational cornerstone within the domain of lot-sizing problems. It is also applicable to a variety of important production planning problems which are…
Boris Chervonenkis, Andrei Krasnov, Alexander Gasnikov, A. V. Lobanov
optimizing a two-variable function on a square Authors: ['Boris Chervonenkis' 'Andrei Krasnov' 'Alexander Gasnikov' 'A. V. Lobanov'] Abstract. The challenges of black box optimization arise due to imprecise responses and limited output information. This article describes new results on optimizing multivariable…
Jiyizhe Zhang, Naoto Sugisawa, Kobi Felton, Shinichiro Fuse + 1 more
Amide bond formation is one of the most prevalent reactions in pharmaceutical industry, among which the Schotten-Baumann reaction has attracted attention as a potential green amide formation approach. However, the use of water in the reaction system often causes undesired hydrolysis and can generate a multiphase…