Results 81 to 90 of about 9,528 (141)

Combined Machine Learning and Molecular Modelling Workflow for the Recognition of Potentially Novel Fungicides

Molecules, 2020
Novel machine learning and molecular modelling filtering procedures for drug repurposing have been carried out for the recognition of the novel fungicide targets of Cyp51 and Erg2.
Ozren Jović, Tomislav Šmuc
doaj   +1 more source

Training Input-Output Recurrent Neural Networks through Spectral Methods [PDF]

, 2016
We consider the problem of training input-output recurrent neural networks (RNN) for sequence labeling tasks. We propose a novel spectral approach for learning the network parameters.
Anandkumar, Anima, Sedghi, Hanie
core   +2 more sources

Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods [PDF]

, 2015
Training neural networks is a challenging non-convex optimization problem, and backpropagation or gradient descent can get stuck in spurious local optima.
Anandkumar, Anima, Janzamin, Majid, Sedghi, Hanie   +2 more
core   +3 more sources

Quantifying the climatic influence on Lassa fever incidences in six high-risk Nigerian states using multilinear regression and generalized additive models

Discover Public Health
Introduction Lassa fever, a viral hemorrhagic disease endemic to West Africa, presents significant public health challenges due to its environmental sensitivity and high mortality rate.
Ibiyinka Fuwape, Samuel Ogunjo, Funmilayo Erinfolami, Olugbenga Osunmakinwa, Opeyemi Ajanaku, Aderonke Akerele, Adetoun Akinlami, Joshua Akinsusi, Josephine Olayinka-Olagunju, Olayinka Asubiaro   +9 more
doaj   +1 more source

Role of constrained modulus in predicting resilient modulus of RAP-included granular materials via ML and conventional methods

Results in Engineering
Conventional regression and modern machine learning (ML) models were developed and evaluated to estimate the resilient modulus (MR) of unbound granular materials.
Muhammad Arshad, Muhammad Zaka Emad
doaj   +1 more source

EEG data classification using multilinear regression model

, 2020
Beyin Bilgisayar Arayüzleri (BCI), kişilerin, sinir sistemlerini kullanmaksızın,elektromekanik veya nöroprostetik bir cihazı bilgisayar yardımıyla denetlemelerini sağlayan sistemlerdir. Kafaderisi üzerine yerleştirilen elektrotlardan elde edilen ve Elektroansefalogram (EEG) adı verilen elektriksel kayıtlar sayesinde beyin dokuları hakkındabilgi ...
openaire   +1 more source

Dictionary-based Tensor Canonical Polyadic Decomposition

, 2017
To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary.
Cohen, Jérémy E., Gillis, Nicolas
core   +1 more source

Application of multilinear regression analysis in modeling of soil properties for geotechnical civil engineering works in Calabar South

Nigerian Journal of Technology, 2018
The application of Multi-Linear Regression Analysis (MLRA) model for predicting soil properties in Calabar South offers a technical guide and solution in foundation designs problems in the area. Forty-five soil samples were collected from fifteen different boreholes at a different depth and 270 tests were carried out for CBR, MC, SG, LL, PL test and GS
Egbe, J.G., Ewa, D.E., Ubi, S.E., Ikwa, G.B., Tumenayo, O.O.   +4 more
openaire   +3 more sources

Sustainable Polyurethane-Based Polymer Concrete: Mechanical and Non-destructive Properties with Machine Learning Technique

International Journal of Concrete Structures and Materials
Polyurethane-based polymer concrete (PUC) has become a popular material for pavement repair. However, its compressive strength (f c) is essential to achieve effective repair work.
S. I. Haruna, Han Zhu, Yasser E. Ibrahim, Jian Yang, AIB Farouk, Jianwen Shao, Musa Adamu, Omar Shabbir Ahmed   +7 more
doaj   +1 more source

Identification of binary cellular automata from spatiotemporal binary patterns using a fourier representation [PDF]

, 2003
The identification of binary cellular automata from spatio-temporal binary patterns is investigated in this paper. Instead of using the usual Boolean or multilinear polynomial representation, the Fourier transform representation of Boolean functions is ...
Billings, S.A., Guo, L.Z.
core