Results 111 to 120 of about 9,520,135 (306)
Advanced Materials Technologies, EarlyView.Hierarchical multi‐material TPMS lattices are engineered as flexible tactile sensors by combining soft and stiff elastomeric layers with a conformal conductive coating. The bilayer architecture delivers sensitivity at low pressures while maintaining a broad detectable range under large loads, enabling reliable pressure and vibration monitoring for ...
Reza Noroozi +3 more
wiley +1 more source
Optimal Growth and Borrowing with Non-Convex Technology
SSRN Electronic Journal, 2006 This paper employs a simple intertemporal optimization model to analyze the optimal growth and borrowing for a small open economy with non-convex technology that imports intermediate inputs for production. Unlike other papers in the literature, this paper concludes that there is only one path for an open economy to achieve optimal growth: namely, the ...
openaire +2 more sources
3D‐Printed Corneal Substitutes: Materials, Fabrication, and Preclinical Progress
Advanced Materials Technologies, EarlyView.Successful clinical translation of 3D‐printed corneal substitutes relies on the interplay between the bioink properties, cellular component, and the fabrication process. These factors influence the critical properties of the construct, including optical transparency, mechanical stability, suture retention, that ultimately govern long‐term stromal ...
Shadi Moshayedi +4 more
wiley +1 more source
Variance-reduced Clipping for Non-convex Optimization
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Gradient clipping is a standard training technique used in deep learning applications such as large-scale language modeling to mitigate exploding gradients. Recent experimental studies have demonstrated a fairly special behavior in the smoothness of the training objective along its trajectory when trained with gradient clipping. That is, the smoothness
Amirhossein Reisizadeh +3 more
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Global Non-convex Optimization with Discretized Diffusions
CoRR, 2018 An Euler discretization of the Langevin diffusion is known to converge to the global minimizers of certain convex and non-convex optimization problems. We show that this property holds for any suitably smooth diffusion and that different diffusions are suitable for optimizing different classes of convex and non-convex functions.
Murat A. Erdogdu +2 more
openaire +4 more sources
Matrix convex functions with applications to weighted centers for semidefinite programming [PDF]
In this paper, we develop various calculus rules for general smooth matrix-valued functions and for the class of matrix convex (or concave) functions first introduced by Loewner and Kraus in 1930s.
Zhang, S., Luo, Z-Q., Brinkhuis, J.
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Exact penalties for decomposable convex optimization problems
, 2021 We consider a general decomposable convex optimization problem. By using right-hand side allocation technique, it can be transformed into a collection of small dimensional optimization problems.
Konnov I.V.
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In Situ Two‐Dimensional Residual Stress Characterization of Thin Films
Advanced Materials Technologies, EarlyView.An integrated in situ curvature metrology platform combining speckle‐based curvature optical metrology (SCOM) with multi‐beam optical sensors (MOS) enables spatially resolved two‐dimensional curvature mapping of thick sputtered coatings. The SCOM technique provides excellent agreement with MOS while providing an extended measurable curvature range ...
Wai Jue Tan +6 more
wiley +1 more source
Learning in Non-convex Games with an Optimization Oracle
CoRR, 2018 We consider online learning in an adversarial, non-convex setting under the assumption that the learner has an access to an offline optimization oracle. In the general setting of prediction with expert advice, Hazan et al. (2016) established that in the optimization-oracle model, online learning requires exponentially more computation than statistical ...
Naman Agarwal, Alon Gonen, Elad Hazan
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The Effect of Transformations on the Approximation of Univariate (Convex) Functions with Applications to Pareto Curves [PDF]
In the literature, methods for the construction of piecewise linear upper and lower bounds for the approximation of univariate convex functions have been proposed.We study the effect of the use of increasing convex or increasing concave transformations ...
Siem, A.Y.D. +2 more
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