Results 51 to 60 of about 22,674 (253)

Stochastic gradient descent algorithm preserving differential privacy in MapReduce framework

Tongxin xuebao, 2018
Aiming at the contradiction between the efficiency and privacy of stochastic gradient descent algorithm in distributed computing environment,a stochastic gradient descent algorithm preserving differential privacy based on MapReduce was proposed.Based on ...
Yihan YU, Yu FU, Xiaoping WU
doaj   +2 more sources

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

Equating quantum imaginary time evolution, Riemannian gradient flows, and stochastic implementations

Physical Review Research
We identify quantum imaginary time evolution as a Riemannian gradient flow on the unitary group. We develop an upper bound for the error between the two evolutions that can be controlled through the step size of the Riemannian gradient descent that ...
Nathan A. McMahon, Mahum Pervez, Christian Arenz   +2 more
doaj   +1 more source

Graph Drawing by Stochastic Gradient Descent [PDF]

IEEE Transactions on Visualization and Computer Graphics, 2019
Submitted to IEEE Transactions on Visualization and Computer Graphics on 26/06 ...
Jonathan X. Zheng, Samraat Pawar, Dan F. M. Goodman   +2 more
openaire   +4 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Distributed Stochastic Gradient Descent With Compressed and Skipped Communication

IEEE Access, 2023
This paper introduces CompSkipDSGD, a new algorithm for distributed stochastic gradient descent that aims to improve communication efficiency by compressing and selectively skipping communication.
Tran Thi Phuong, Le Trieu Phong, Kazuhide Fukushima   +2 more
doaj   +1 more source

Stochastic Adaptive Gradient Descent Without Descent

CoRR
We introduce a new adaptive step-size strategy for convex optimization with stochastic gradient that exploits the local geometry of the objective function only by means of a first-order stochastic oracle and without any hyper-parameter tuning. The method comes from a theoretically-grounded adaptation of the Adaptive Gradient Descent Without Descent ...
Jean-François Aujol, Jérémie Bigot, Camille Castera   +2 more
openaire   +2 more sources

On Scalable Inference with Stochastic Gradient Descent

CoRR, 2017
In many applications involving large dataset or online updating, stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates and has gained increasing popularity due to its numerical convenience and memory efficiency. While the asymptotic properties of SGD-based estimators have been established decades ago, statistical ...
Yixin Fang, Jinfeng Xu, Lei Yang
openaire   +2 more sources

Designing Polymer Nanocomposites for X‐Ray Shielding: Mechanisms, Architectures, and Scalable Processing

Advanced Engineering Materials, EarlyView.
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele, Hossein Ipakchi, Tizazu H. Mekonnen   +2 more
wiley   +1 more source