Results 121 to 130 of about 1,925,652 (255)

Machine Learning for Green Solvents: Assessment, Selection and Substitution

Advanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta, Janhavi Nistane, Abhishek Sose, Harikrishna Sahu, Rampi Ramprasad   +4 more
wiley   +1 more source

Hyperparameters tuning of random forest with harmony search in credit scoring [PDF]

, 2019
Correct identification of defaulters and non-defaulters in the lending industry is a crucial task for financial institutions. Credit scoring is a tool utilized for credit granting decisions.
Goh, Rui Ying, Adam, Mohd. Bakri, Lee, Lai Soon   +2 more
core   +1 more source

Hyperparameter optimization with approximate gradient

CoRR, 2016
Most models in machine learning contain at least one hyperparameter to control for model complexity. Choosing an appropriate set of hyperparameters is both crucial in terms of model accuracy and computationally challenging. In this work we propose an algorithm for the optimization of continuous hyperparameters using inexact gradient information.
openaire   +3 more sources

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Robust optimization of SVM hyperparameters in the classification of bioactive compounds [PDF]

, 2015
Background: Support Vector Machine has become one of the most popular machine learning tools used in virtual screening campaigns aimed at finding new drug candidates. Although it can be extremely effective in finding new potentially active compounds, its
Podlewska, Sabina, Czarnecki, Wojciech, Wojciech M Czarnecki, Bojarski, Andrzej J., Sabina Podlewska, Andrzej J Bojarski   +5 more
core   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Regularization can help mitigate poisoning attacks... with the right hyperparameters [PDF]

, 2021
Machine learning algorithms are vulnerable to poisoning attacks, where a fraction of the training data is manipulated to degrade the algorithms' performance.
Spencer, Phillippa, Lupu, Emil C, Carnerero-Cano, Javier, Muñoz-González, Luis   +3 more
core  

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Biometric Recognition Using Multimodal Physiological Signals

IEEE Access, 2019
In this paper, we address the problem of biometric recognition using the multimodal physiological signals. To this end, four different signals are considered: heart rate (HR), breathing rate (BR), palm electrodermal activity (P-EDA), and perinasal ...
Simone Bianco, Paolo Napoletano
doaj   +1 more source

Recent advances in surrogate-based optimization [PDF]

, 2009
The evaluation of aerospace designs is synonymous with the use of long running computationally intensive simulations. This fuels the desire to harness the efficiency of surrogate-based methods in aerospace design optimization.
Alexander I.J. Forrester, Andy J. Keane, Keane, Andy J., Forrester, Alexander I.J.   +3 more
core   +1 more source