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Stochastic Gradient Descent-like relaxation is equivalent to Metropolis dynamics in discrete optimization and inference problems
Is Stochastic Gradient Descent (SGD) substantially different from Metropolis Monte Carlo dynamics? This is a fundamental question at the time of...
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Finite element analysis of femoral neck strains during stair ascent and descent
For older population, a better understanding of the hip joint loading environment is needed for the prevention of hip pain, and the reduction of the...
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Uncertainty quantification in multivariable regression for material property prediction with Bayesian neural networks
With the increased use of data-driven approaches and machine learning-based methods in material science, the importance of reliable uncertainty...
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Stromal heterogeneity may explain increased incidence of metaplastic breast cancer in women of African descent
The biologic basis of genetic ancestry-dependent variability in disease incidence and outcome is just beginning to be explored. We recently reported...
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Complexity control by gradient descent in deep networks
Overparametrized deep networks predict well, despite the lack of an explicit complexity control during training, such as an explicit regularization...
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Identification of a novel Sorcin isoform with a different C-terminal but intact dimerization property
Sorcin (Sri), a member of penta EF-hand protein family plays a diverse role in maintaining calcium homeostasis, cell cycle and vesicular trafficking....
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Preliminary study of the effect of low-intensity focused ultrasound on postpartum uterine involution and breast pain in puerperal women: a randomised controlled trial
To evaluate the safety and efficacy of low-intensity focused ultrasound (LIFU) therapy in facilitating fundus descent and relieving postpartum breast...
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Some convergently three-term trust region conjugate gradient algorithms under gradient function non-Lipschitz continuity
This paper introduces two three-term trust region conjugate gradient algorithms, TT-TR-WP and TT-TR-CG, which are capable of converging under...
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Towards provably efficient quantum algorithms for large-scale machine-learning models
Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power,...
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Fast gradient algorithm for complex ICA and its application to the MIMO systems
This paper proposes a new gradient-descent algorithm for complex independent component analysis and presents its application to the Multiple-Input...
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UAV path planning based on third-party risk modeling
Drones play an important role in modern cities, they bring convenience but also bring corresponding risks. Falling drones can cause casualties or...
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Estimating the strength of soil stabilized with cement and lime at optimal compaction using ensemble-based multiple machine learning
It has been imperative to study and stabilize cohesive soils for use in the construction of pavement subgrade and compacted landfill liners...
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Stochastic representation of many-body quantum states
The quantum many-body problem is ultimately a curse of dimensionality: the state of a system with many particles is determined by a function with...
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Network properties determine neural network performance
Machine learning influences numerous aspects of modern society, empowers new technologies, from Alphago to ChatGPT, and increasingly materializes in...
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A distributed nanocluster based multi-agent evolutionary network
As an important approach of distributed artificial intelligence, multi-agent system provides an efficient way to solve large-scale computational...
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Visual augmentation of deck-landing-ability improves helicopter ship landing decisions
When attempting to land on a ship deck tossed by the sea, helicopter pilots must make sure that the helicopter can develop sufficient lift to be able...
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Genetic analysis of over half a million people characterises C-reactive protein loci
Chronic low-grade inflammation is linked to a multitude of chronic diseases. We report the largest genome-wide association study (GWAS) on C-reactive...
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Hybrid fuzzy deep neural network toward temporal-spatial-frequency features learning of motor imagery signals
Achieving an efficient and reliable method is essential to interpret a user’s brain wave and deliver an accurate response in biomedical signal...
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Noise-robust optimization of quantum machine learning models for polymer properties using a simulator and validated on the IonQ quantum computer
Quantum machine learning for predicting the physical properties of polymer materials based on the molecular descriptors of monomers was investigated....
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A Variable Neighbourhood Descent Heuristic for Conformational Search Using a Quantum Annealer
Discovering the low-energy conformations of a molecule is of great interest to computational chemists, with applications in in silico materials...
