A fast continuous time approach for non-smooth convex optimization using Tikhonov regularization technique. [PDF]
Comput Optim ApplKarapetyants MA.
europepmc +1 more source
In this paper, convex interval games are introduced and some characterizations are given. Some economic situations leading to convex interval games are discussed.
Brânzei, R. +2 more
core
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Advanced Intelligent Discovery, EarlyView.Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
A convex optimization approach to radiation treatment planning with dose constraints. [PDF]
Optim Eng, 2019 Fu A, Ungun B, Xing L, Boyd S.
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Robust Solutions of Optimization Problems Affected by Uncertain Probabilities
In this paper we focus on robust linear optimization problems with uncertainty regions defined by ø-divergences (for example, chi-squared, Hellinger, Kullback-Leibler).
De Waegenaere, A.M.B. +4 more
core
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Adaptive Restart of the Optimized Gradient Method for Convex Optimization. [PDF]
J Optim Theory Appl, 2018 Kim D, Fessler JA.
europepmc +1 more source
Survival estimation through the cumulative hazard with monotone natural cubic splines using convex optimization-the HCNS approach. [PDF]
Comput Methods Programs Biomed, 2020 Bantis LE, Tsimikas JV, Georgiou SD.
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Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source