15 papers · ranked by Valyu relevance
Qian Li, Sanyang Liu, Xin‐She Yang
All metaheuristic optimization algorithms require some initialization, and the initialization for such optimizers is usually carried out randomly. However, initialization can have some significant influence on the performance of such algorithms. This paper presents a systematic comparison of 22 different initialization…
Mengyu Huang, Yuxing Zhong, Huiwen Yang, Jiazheng Wang + 3 more
'Bo Bai' 'Ling Shi'] The simplex method is one of the most fundamental technologies for solving linear programming (LP) problems and has been widely applied to different practical applications. In the past literature, how to improve and accelerate the simplex method has attracted plenty of research. One important way…
M. Emre Celebi, Hassan A. Kingravi
K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. Many of these methods, however…
Rui Li, Zhibin Pan, Yang Wang
Tensor decomposition (TD) is widely used in hyperspectral image (HSI) compression. The initialization of factor matrix in tensor decomposition can determine the HSI compression performance. It is worth noting that HSI is highly correlated in bands. However, this phenomenon is ignored by the previous TD method. Aiming…
Marius Pachitariu, Lin Zhong, Alexa Gracias, Amanda Minisi + 2 more
Artificial neural networks learn faster if they are initialized well. Good initializations can generate high-dimensional macroscopic dynamics with long timescales. It is not known if biological neural networks have similar properties. Here we show that the eigenvalue spectrum and dynamical properties of large-scale…
Abiy Tasissa, Rongjie Lai, Chunyu Wang
The problem of finding the configuration of points given partial information on pairwise inter-point distances, the Euclidean distance geometry problem, appears in multiple applications. In this paper, we propose an approach that integrates homology modeling and a nonconvex distance geometry algorithm for the protein…
Ilia Zintchenko, Matthew B. Hastings, Nathan Wiebe, Ethan Brown + 1 more
'Matthias Troyer'] Heuristic optimisers which search for an optimal configuration of variables relative to an objective function often get stuck in local optima where the algorithm is unable to find further improvement. The standard approach to circumvent this problem involves periodically restarting the algorithm from…
Tomáš Flouri, Kassian Kobert, Torbjørn Rognes, Alexandros Stamatakis
Pairwise sequence alignment is perhaps the most fundamental bioinformatics operation. An optimal global alignment algorithm was described in 1970 by Needleman and Wunsch. In 1982 Gotoh presented an improved algorithm with lower time complexity. Gotoh’s algorithm is frequently cited (1447 citations, Google Scholar, May…
Neha Vinayak, Shandar Ahmad
A multi-layer perceptron (MLP) consists of a number of forward-connected weights (W_ijk_) from each feeding layer node (n_ij_) to the many initially equivalent nodes (n_i+1,k_) in the next layer. Exact a priori order and search space of these weights (W_ijk_) is random and prone to redundancy, irreproducibility and…
Mohammed Baragilly, Brian H Willis
Meta-analysis may be used to summarise a test’s accuracy. Often the sensitivity and specificity are the measures of interest and as these are correlated a bivariate random effects model is commonly used to fit the data. This model has five parameters and it may be optimised using a Newton-Raphson based algorithm…
Jiawei Zhang
In this paper, we will provide an introduction to the derivative-free optimization algorithms which can be potentially applied to train deep learning models. Existing deep learning model training is mostly based on the back propagation algorithm, which updates the model variables layers by layers with the gradient…
M.Z. Naser, Abdallah Naser
Problems Authors: ['M.Z. Naser' 'Abdallah Naser'] This paper presents the Firefighter Optimization (FFO) algorithm as a new hybrid metaheuristic for optimization problems. This algorithm stems inspiration from the collaborative strategies often deployed by firefighters in firefighting activities. To evaluate the…
Fabio F. de Oliveira, Leonardo A. Dias, Marcelo A. C. Fernandes
In bioinformatics, alignment is an essential technique for finding similarities between biological sequences. Usually, the alignment is performed with the Smith-Waterman (SW) algorithm, a well-known sequence alignment technique of high-level precision based on dynamic programming. However, given the massive data volume…
Koichi Miyamoto, Naoki Yamamoto, Yasubumi Sakakibara
We propose two quantum algorithms for a problem in bioinformatics, position weight matrix (PWM) matching, which aims to find segments (sequence motifs) in a biological sequence such as DNA and protein that have high scores defined by the PWM and are thus of informational importance related to biological function. The…
Nikolai Baudis, Pierre Barbera, Sebastian Graf, Sarah Lutteropp + 3 more
In the context of a master level programming practical at the computer science department of the Karlsruhe Institute of Technology, we developed and make available two independent and highly optimized open-source implementations for the pair-wise statistical alignment model, also known as TKF91, that was developed by…