Results 71 to 80 of about 73,328 (265)

Topic Modelling Black Box Optimization

CoRR
Choosing the number of topics $T$ in Latent Dirichlet Allocation (LDA) is a key design decision that strongly affects both the statistical fit and interpretability of topic models. In this work, we formulate the selection of $T$ as a discrete black-box optimization problem, where each function evaluation corresponds to training an LDA model and ...
Roman Akramov, Artem Khamatullin, Svetlana Glazyrina, Maksim Kryzhanovskiy, Roman Ischenko   +4 more
openaire   +2 more sources

Black-Box Optimization with Local Generative Surrogates

, 2020
We propose a novel method for gradient-based optimization of black-box simulators using differentiable local surrogate models. In fields such as physics and engineering, many processes are modeled with non-differentiable simulators with intractable likelihoods.
Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atilim Gunes Baydin   +4 more
openaire   +3 more sources

Optimization on Black Box Function Optimization Problem [PDF]

Mathematical Problems in Engineering, 2015
There are a large number of engineering optimization problems in real world, whose input-output relationships are vague and indistinct. Here, they are called black box function optimization problem (BBFOP). Then, inspired by the mechanism of neuroendocrine system regulating immune system, BP neural network modified immune optimization algorithm (NN-MIA)
Jin-ke Xiao, Wei-min Li, Wei Li, Xin-rong Xiao   +3 more
openaire   +1 more source

The skills required for transition to university and study in biological sciences: A student perspective

FEBS Open Bio, EarlyView.
Bioscience students were asked for their opinions on the value and teaching of skills. 204 responded that teamwork, time management and study skills are necessary to reach University, that scientific writing, research, laboratory and presentation skills are taught effectively during their studies, while other skills are gained inherently through study ...
Janella Borrell, Susan Crennell
wiley   +1 more source

Bayesian Optimization for Instruction Generation

Applied Sciences
The performance of Large Language Models (LLMs) strongly depends on the selection of the best instructions for different downstream tasks, especially in the case of black-box LLMs.
Antonio Sabbatella, Francesco Archetti, Andrea Ponti, Ilaria Giordani, Antonio Candelieri   +4 more
doaj   +1 more source

Improved Differential Evolution for Large-Scale Black-Box Optimization

IEEE Access, 2018
The demand for solving large-scale complex problems continues to grow. Many real-world problems are described by a large number of variables that interact with each other in a complex way.
Mirjam Sepesy Maucec, Janez Brest, Borko Boskovic, Zdravko kacic   +3 more
doaj   +1 more source

Molecular dynamics simulations of positively selected codons in FcγRI reveal novel biochemical binding properties

FEBS Open Bio, EarlyView.
Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young, Omar Arias‐Gaguancela, Fiona Gibson, Morgan Grainger, Jodie Score, Amit Nathubhai, Mauricio Cafiero, Lee Richard Machado   +7 more
wiley   +1 more source

Optimizing photoactivation of PA‐mCherry for optical pooled CRISPR screens

FEBS Open Bio, EarlyView.
Photoactivatable PA‐mCherry finds widespread use to optically tag individual cells. However, confocal 405 nm UV laser‐scanning (normal scan) is much less efficient than widefield UV illumination, limiting the use of PA‐mCherry on confocal instruments. We remedy this limitation by reporting that rapid and repeated confocal scanning with a low‐intensity,
Sravasti Mukherjee, Giulia Zanetti, Bram van den Broek, Kees Jalink   +3 more
wiley   +1 more source

OptunaHub: A Platform for Black-Box Optimization

CoRR
Black-box optimization (BBO) underpins advances in domains such as AutoML and Materials Informatics, yet implementations of algorithms and benchmarks remain fragmented across research communities. We introduce OptunaHub (https://hub.optuna.org/), a community-oriented, decentralized platform for distributing BBO components under a unified Optuna ...
Yoshihiko Ozaki, Shuhei Watanabe, Toshihiko Yanase   +2 more
openaire   +2 more sources

Black-box Optimizers vs Taste Shocks

CoRR, 2023
We evaluate and extend the solution methods for models with binary and multiple continuous choice variables in dynamic programming, particularly in cases where a discrete state space solution method is not viable. Therefore, we approximate the solution using taste shocks or black-box optimizers that applied mathematicians use to benchmark their ...
openaire   +2 more sources