Results 41 to 50 of about 19,578 (192)
Mathematical Methods in the Applied Sciences, Volume 49, Issue 4, Page 2135-2160, 15 March 2026.ABSTRACT It is an elementary fact in the scientific literature that the Lipschitz norm of the realization function of a feedforward fully connected rectified linear unit (ReLU) artificial neural network (ANN) can, up to a multiplicative constant, be bounded from above by sums of powers of the norm of the ANN parameter vector.
Arnulf Jentzen, Timo Kröger
wiley +1 more source
MathematicsThis paper presents an enhanced algorithm designed to solve variational inequality problems that involve a pseudomonotone and Lipschitz continuous operator in real Hilbert spaces.
Habib ur Rehman +2 more
doaj +1 more source
IEEE Access, 2018 One of the fundamental challenges of deploying sensor networks in applications, such as environmental monitoring and surveillance, is power management in the presence of various constraints.
Milad Esmaeilpour +2 more
doaj +1 more source
Applied Stochastic Models in Business and Industry, Volume 42, Issue 2, March/April 2026.ABSTRACT The so‐called algorithmic bias is a hot topic in the decision‐making process based on Artificial Intelligence, especially when demographics, such as gender, age or ethnic origin, come into play. Frequently, the problem is not only in the algorithm itself, but also in the biased data that feed the algorithm, which is just the reflection of the ...
Elena M. De‐Diego +2 more
wiley +1 more source
Optimal beamforming in over-the-air federated learning for efficient model aggregation
ICT ExpressFederated learning (FL) enables distributed model training while preserving privacy, but frequent updates from many devices create substantial communication challenges.
Sangwoo Choi, Minsik Kim, Daeyoung Park
doaj +1 more source
On Stochastic Subgradient Mirror-Descent Algorithm with Weighted Averaging [PDF]
, 2013 This paper considers stochastic subgradient mirror-descent method for solving constrained convex minimization problems. In particular, a stochastic subgradient mirror-descent method with weighted iterate-averaging is investigated and its per-iterate ...
Angelia Nedic ́ +2 more
core
Differentially Private Convex Optimization with Piecewise Affine Objectives
, 2014 Differential privacy is a recently proposed notion of privacy that provides strong privacy guarantees without any assumptions on the adversary. The paper studies the problem of computing a differentially private solution to convex optimization problems ...
Han, Shuo +2 more
core +1 more source
Estimating Plant Species Richness With Sentinel and Landsat Data Across Ecosystems in China
Ecology and Evolution, Volume 16, Issue 3, March 2026.438 field plots were used to estimate plant diversity across ecosystems; 18 spectral indices were derived from Sentinel and Landsat data; EVI, DVI, PSRI, NDVI, PRI, GNDVI, and GMEVI were identified as powerful indicators for predicting plant alpha diversity.
Keman Wang +4 more
wiley +1 more source
Delayed Star Subgradient Methods for Constrained Nondifferentiable Quasi-Convex Optimization
AlgorithmsIn this work, we consider the problem of minimizing a quasi-convex function over a nonempty closed convex constrained set. In order to approximate a solution of the considered problem, we propose delayed star subgradient methods.
Ontima Pankoon, Nimit Nimana
doaj +1 more source
Distributed Event-Triggered Subgradient Method for Convex Optimization With General Step-Size
IEEE Access, 2020 In this paper, the consensus and optimization of a multiagent system in a distributed optimization problem with bounded constraint is discussed under the general step-size, which is square nonsummable.
Ran Li, Xiaowu Mu
doaj +1 more source