Results 81 to 90 of about 22,732 (252)
Advanced Materials, EarlyView.A Nb‐proximitized Josephson junction based on a WTe2/α‐Fe2O3 heterostructure exhibits a robust superconducting diode effect with programmable polarity. The diode direction can be trained by magnetic fields and switched by temperature cycling, revealing tunable finite‐momentum pairing states and competing superconducting states in symmetry‐broken ...
Enze Zhang +9 more
wiley +1 more source
Applied SciencesThe uncertainty in the new power system has increased, leading to limitations in traditional stability analysis methods. Therefore, considering the perspective of the three-dimensional static security region (SSR), we propose a novel approach for system ...
Jiahui Wu +3 more
doaj +1 more source
Advanced Materials, EarlyView.ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh +2 more
wiley +1 more source
Semi-Cyclic Stochastic Gradient Descent
CoRR, 2019 We consider convex SGD updates with a block-cyclic structure, i.e. where each cycle consists of a small number of blocks, each with many samples from a possibly different, block-specific, distribution. This situation arises, e.g., in Federated Learning where the mobile devices available for updates at different times during the day have different ...
Hubert Eichner +4 more
openaire +3 more sources
On the Hyperparameters in Stochastic Gradient Descent with Momentum
CoRR, 2021 34 pages, 4 figures.
openaire +3 more sources
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Unforgeability in Stochastic Gradient Descent
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023 Teodora Baluta +4 more
openaire +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
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 +13 more
wiley +1 more source
Adam Algorithm with Step Adaptation
AlgorithmsAdam (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 +2 more
doaj +1 more source