Results 51 to 60 of about 2,178 (210)
Adaptive Weighted Total Variation Penalty for Precise Change Point Detection
Australian &New Zealand Journal of Statistics, Volume 68, Issue 2, June 2026.ABSTRACT Total variation (TV)‐based methods, such as the fused lasso, are standard for change point detection but are impaired by issues like local monotonicity. To address these limitations, this study comparatively analyses the fused lasso with two alternative methodologies.
Dong‐Young Lee +2 more
wiley +1 more source
Data analysis and anomalies detection in cattle behavior
Міжнародний науково-технічний журнал "Проблеми керування та інформатики"Monitoring cattle behavior is critical for ensuring animal health, welfare, and productivity. Anomalies in behavior — such as changes in feeding, locomotion, or social interactions — often precede the onset of disease, stress, or injury. Early detection
Петро Іванович Стецюк +2 more
doaj +1 more source
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
A modified subgradient extragradient method for solving monotone variational inequalities
Journal of Inequalities and Applications, 2017 In the setting of Hilbert space, a modified subgradient extragradient method is proposed for solving Lipschitz-continuous and monotone variational inequalities defined on a level set of a convex function.
Songnian He, Tao Wu
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
Properties of the Quadratic Transformation of Dual Variables
Algorithms, 2023 We investigate a solution of a convex programming problem with a strongly convex objective function based on the dual approach. A dual optimization problem has constraints on the positivity of variables.
Vladimir Krutikov +5 more
doaj +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
Regret Function Minimization Algorithms
Кібернетика та комп'ютерні технологіїIntroduction. The article addresses the problem of making optimal decisions under uncertainty by minimizing the Savage regret function. This function, which evaluates the difference between the actual outcome and the best possible outcome across all ...
Anatolie Baractari +2 more
doaj +1 more source
Dimer models and conformal structures
Communications on Pure and Applied Mathematics, Volume 79, Issue 2, Page 340-446, February 2026.Abstract Dimer models have been the focus of intense research efforts over the last years. Our paper grew out of an effort to develop new methods to study minimizers or the asymptotic height functions of general dimer models and the geometry of their frozen boundaries.
Kari Astala +3 more
wiley +1 more source
Dual subgradient method with averaging for optimal resource allocation
, 2017 A dual subgradient method is proposed for solving convex optimization problems with linear constraints. As novelty, the recovering of primal solutions can be avoided. Instead, the optimal convergence rate for the whole sequence of primal-dual iterates is
Nesterov, Yurii +3 more
core +1 more source