Results 61 to 70 of about 605 (168)
Quantitative Biology, Volume 14, Issue 2, June 2026.Abstract Computed tomography (CT) images are often severely corrupted by artifacts in the presence of metals. Existing supervised metal artifact reduction (MAR) approaches suffer from performance instability on known data due to their reliance on limited paired metal‐clean data, which limits their clinical applicability. Moreover, existing unsupervised
Jie Wen +3 more
wiley +1 more source
On the Foundational Arguments of Sufficient Dimension Reduction
WIREs Computational Statistics, Volume 18, Issue 2, June 2026.Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley +1 more source
Fractal and FractionalEconomic dispatch in wind-integrated power systems is a critical challenge, yet many recent metaheuristics suffer from premature convergence, heavy parameter tuning, and limited ability to escape local optima in non-smooth valve-point landscapes.
Abdul Wadood +4 more
doaj +1 more source
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.Abstract Accurate quantification of uncertainty in neural network predictions remains a central challenge for scientific applications involving high‐dimensional, correlated data. While existing methods capture either aleatoric or epistemic uncertainty, few offer closed‐form, multidimensional distributions that preserve spatial correlation while ...
Harrison J. Goldwyn +4 more
wiley +1 more source
IEEE AccessThe global drive towards carbon neutrality has led to a significant increase in the number of power plants based on renewable energy sources (RES). Concurrently, numerous households are adopting RES to generate their own energy, aiming to decrease both ...
A. Daniel Carnerero +7 more
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Breaking the Nonconvexity Barrier: Certified Global Optimality in Mixed-Integer Programming
Mixed-Integer Programming (MIP) is a powerful framework for modeling real-world optimization problems that involve both continuous and discrete decision variables. While convex MIPs are largely tractable using sophisticated branch-and-cut algorithms, the presence of nonconvexity in the objective function or constraints introduces significant ...
Revista, Zen, MATH, 10
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EURASIP Journal on Advances in Signal Processing, 2010 The problem of jointly optimizing the source precoder, relay transceiver, and destination equalizer has been considered in this paper for a multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay channel, where the channel estimates of all ...
Vandendorpe Luc, Chalise BatuK
doaj
Certified Global Optimality for Nonconvex Integer Programs via Extended Formulations
Nonconvex integer programs (NCIPs) pose significant challenges in optimization due to the inherent difficulties arising from both nonconvexity and integrality constraints. Finding globally optimal solutions for such problems is often computationally intractable, and even establishing bounds on the global optimum can be highly complex.
Revista, Zen, MATH, 10
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Impact of endogenous learning curves on maritime transition pathways
Environmental Research LettersThe maritime industry is a crucial hard-to-abate sector that is expected to depend on high-energy density renewable liquid fuels in the future. Traditionally, decarbonization pathways have been assessed assuming exogenous cost trajectories for renewable ...
Sebastian Franz, Rasmus Bramstoft
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A class of nonconvex semidefinite programming in which every KKT point is globally optimal
We consider a special class of nonconvex semidefinite programming problems and show that every point satisfying the Karush--Kuhn--Tucker (KKT) conditions is globally optimal despite nonconvexity. This property is related to pseudoconvex optimization. This class of problems is motivated by an eigenfrequency topology optimization problem in structural ...
Nishioka, Akatsuki, Kanno, Yoshihiro
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