Results 101 to 110 of about 28,952 (292)

Path‐Decoupled Cation‐Eutaxy III–V van der Waals Memristive Semiconductors for Mitigating the Neuromorphic Accuracy‐Energy Trade‐off

Advanced Materials, EarlyView.
Path‐decoupled III–V van der Waals memtransistors spatially separate ionic and electronic transport to overcome the conventional trade‐off between accuracy and energy in neuromorphic hardware. Mobile K+ ions in the vdW gaps set a wide conductance window, Gmax/Gmin, while gate‐tunable hole conduction lowers programming energy, enabling reliable ...
Jihong Bae, Ji Hoon Han, Taeyoung Kim, Jongbum Won, Seokmin Park, Gyu Won Kim, Sungsoon Kim, Hong Choi, Taehoon Kim, Hong‐Sub Lee, Jae‐Hyun Lee, Young Jin Choi, Jinwoo Cheon, Wooyoung Shim   +13 more
wiley   +1 more source

Adam Algorithm with Step Adaptation

Algorithms
Adam (Adaptive Moment Estimation) is a well-known algorithm for the first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments.
Vladimir Krutikov, Elena Tovbis, Lev Kazakovtsev   +2 more
doaj   +1 more source

On the regularizing property of stochastic gradient descent

Inverse Problems, 2018
Stochastic gradient descent is one of the most successful approaches for solving large-scale problems, especially in machine learning and statistics. At each iteration, it employs an unbiased estimator of the full gradient computed from one single randomly selected data point.
Bangti Jin, Xiliang Lu
openaire   +3 more sources

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

A Bootstrap Perspective on Stochastic Gradient Descent

CoRR
Machine learning models trained with \emph{stochastic} gradient descent (SGD) can generalize better than those trained with deterministic gradient descent (GD). In this work, we study SGD's impact on generalization through the lens of the statistical bootstrap: SGD uses gradient variability under batch sampling as a proxy for solution variability under
Hongjian Lan, Yucong Liu, Florian Schäfer 0001   +2 more
openaire   +2 more sources

Designable van der Waals Crystal for Artificial Neuronal Cell Mimicking

Advanced Materials, EarlyView.
Designable van der Waals crystal has been demonstrated for device‐scale neuronal cell mimicking. The structural similarity between ion‐channel in biological membranes and layered vdW lattices is realized with nano‐crystallization via Ar + H2S plasma sulfurization.
Jinhyoung Lee, Gunhyoung Kim, Dongho Lee, Seowoo Son, Hyunho Seok, Sihoon Son, Hyunbin Choi, Geonwook Kim, Geumji Back, Hyunkyu Kim, Chaerin Park, Junmin Ahn, Seongyun Je, Chaeyoung Im, Junil Cho, Magdalena Grzeszczyk, Seongho Kim, Eunseo Go, Hyunwoo Shim, Donghwan Choi, Muyoung Kim, Hyoeng‐U. Kim, Won‐Jun Jang, Taesung Kim   +23 more
wiley   +1 more source

Convergence of Stochastic Gradient Descent for PCA

CoRR, 2015
We consider the problem of principal component analysis (PCA) in a streaming stochastic setting, where our goal is to find a direction of approximate maximal variance, based on a stream of i.i.d. data points in $\reals^d$. A simple and computationally cheap algorithm for this is stochastic gradient descent (SGD), which incrementally updates its ...
openaire   +3 more sources

A 3D‐Printed Blister Test Platform for Quantifying Biointerface Adhesion Mechanisms

Advanced Materials Interfaces, EarlyView.
A 3D‐printed blister platform enables energy‐resolved characterization of soft hydrogel–rigid interfaces. Integrating precision pressure control with hyperelastic modeling directly quantifies adhesion energy (G) and R‐curve toughening. Results reveal that modulating hydrogel concentration and surface roughness drives a tunable transition from cohesive ...
Yoontae Kim, Rahul Patil, Argyris K. Lazaris, Xinran Zhang, Stella Alimperti   +4 more
wiley   +1 more source

Adaptive Natural Gradient Method for Learning of Stochastic Neural Networks in Mini-Batch Mode

Applied Sciences, 2019
Gradient descent method is an essential algorithm for learning of neural networks. Among diverse variations of gradient descent method that have been developed for accelerating learning speed, the natural gradient learning is based on the theory of ...
Hyeyoung Park, Kwanyong Lee
doaj   +1 more source

Neutron Reflectometry and Compression of Graded Hydrogel Surfaces

Advanced Materials Interfaces, EarlyView.
Highly‐entangled and covalently‐crosslinked hydrogels with thin and thick surface gel layers are compressed in neutron reflectometry experiments. Surface gel layer thickness dictates the extent to which the polymer network at the surface of a hydrogel collapses, while crosslinking chemistry, and therefore elastic modulus, impacts the pressure at which ...
Kathryn E. Shaffer, Alex Q. Zhang, Mehdi Karimi, Ahmed Al Kindi, Linnaea D. Uliassi, Nemea S. Courelli, Julia J. Ong, Conor D. Pugsley, Andrew R. Rhode, Erik B. Watkins, Rebecca J.L. Welbourn, Alexander Alexeev, Angela A. Pitenis   +12 more
wiley   +1 more source