Results 121 to 130 of about 22,826 (253)
Stochastic Modified Flows for Riemannian Stochastic Gradient Descent
We give quantitative estimates for the rate of convergence of Riemannian stochastic gradient descent (RSGD) to Riemannian gradient flow and to a diffusion process, the so-called Riemannian stochastic modified flow (RSMF). Using tools from stochastic differential geometry we show that, in the small learning rate regime, RSGD can be approximated by the ...
Benjamin Gess +2 more
openaire +5 more sources
Information Transmission Strategies for Self‐Organized Robotic Aggregation
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng +5 more
wiley +1 more source
A Novel Framework for Abnormal Risk Classification over Fetal Nuchal Translucency Using Adaptive Stochastic Gradient Descent Algorithm. [PDF]
Verma D +5 more
europepmc +1 more source
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
A Scalable Bayesian Sampling Method Based on Stochastic Gradient Descent Isotropization. [PDF]
Franzese G +3 more
europepmc +1 more source
Anti‐PD‐1/PD‐L1 blockade has revolutionized cancer immunotherapy, but is ineffective against endocrine‐treated (i.e., Tamoxifen), relapsed ER+ breast cancer (BC) patients. This study provides insight into the sub‐optimal response of ER+BCs to anti‐PD‐1/PD‐L1 blockade – highlighting the induction of STING and the CEACAM1/TIM3 axis after chronic ...
Marvin Angelo E Aberin +20 more
wiley +1 more source
In wavefront sensorless adaptive optics (WFS-less AO) systems, stochastic parallel gradient descent (SPGD) is the primary optimization method for correcting wavefront distortions. However, as the intensity of atmospheric turbulence interference increases,
Peng Chen +6 more
doaj +1 more source
An Improvised Sentiment Analysis Model on Twitter Data Using Stochastic Gradient Descent (SGD) Optimization Algorithm in Stochastic Gate Neural Network (SGNN). [PDF]
Vidyashree KP, Rajendra AB.
europepmc +1 more source
This work proposed a pollen‐enhanced bionic mechanoreceptor based on ionic convection. Leveraging the ion anchoring effect of the pollen particle, the output performance could be ∼12 times higher than the original state. By employing deep learning models as AI brains, the feasibility of a sensory‐augmented prosthesis consisting of a pollen‐enhanced ...
Zi Hao Guo +7 more
wiley +1 more source
Using the Stochastic Gradient Descent Optimization Algorithm on Estimating of Reactivity Ratios. [PDF]
Fazakas-Anca IS, Modrea A, Vlase S.
europepmc +1 more source

