Results 121 to 130 of about 2,019,981 (302)

Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning

, 2022
Tackling new machine learning problems with neural networks always means optimizing numerous hyperparameters that define their structure and strongly impact their performances.
Congedo, Pietro Marco, Poëtte, Gaël, Novello, Paul, Lugato, David   +3 more
core  

Model Predictive Control for Magnetically Actuated Cellbots

Advanced Robotics Research, EarlyView.
Magnetically actuated cellbots, formed by embedding microrobots in living cells, are steered along precise paths using a model predictive controller enhanced with a Gaussian process disturbance estimator. The data‐efficient method calibrates each cellbot individually, cutting modeling error by roughly 60% and enabling accurate navigation through cell ...
Mehdi Kermanshah, Logan E. Beaver, Max Sokolich, Fatma Ceren Kirmizitas, Ahmad Ahmad, Roberto Tron, Ron Weiss, Sambeeta Das, Calin Belta   +8 more
wiley   +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

Stochastic Hyperparameter Optimization through Hypernetworks

CoRR, 2018
Machine learning models are often tuned by nesting optimization of model weights inside the optimization of hyperparameters. We give a method to collapse this nested optimization into joint stochastic optimization of weights and hyperparameters. Our process trains a neural network to output approximately optimal weights as a function of hyperparameters.
Jonathan Lorraine, David Duvenaud
openaire   +2 more sources

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

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

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

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