Results 161 to 170 of about 7,649 (300)

Synthesizing Interacting Model‐Based Optimal Control and Model‐Free Learning Approaches for Nonlinear Systems

open access: yesInternational Journal of Robust and Nonlinear Control, Volume 36, Issue 10, Page 5619-5634, 10 July 2026.
ABSTRACT In this paper, we consider the optimal control problem for an unknown continuous‐time nonlinear system, and present a framework that integrates model‐based and model‐free methods to solve it. Each approach offers distinct advantages: model‐based techniques provide offline synthesis and data efficiency, while model‐free procedures excel at ...
Surabhi Athalye   +2 more
wiley   +1 more source

On the Choice of Optimization Norm for Anderson Acceleration of the Picard Iteration for Navier–Stokes Equations

open access: yesNumerical Methods for Partial Differential Equations, Volume 42, Issue 4, July 2026.
ABSTRACT While recent Anderson acceleration (AA) convergence theory [Pollock et al., IMA Num. An., 2021] requires that the AA optimization norm match the Hilbert space norm associated with the fixed point operator, in implementations the ℓ2$$ {\ell}^2 $$ norm is the most common choice. So far there is little research done regarding this discrepancy. To
Elizabeth Hawkins, Leo G. Rebholz
wiley   +1 more source

Parabolic PDEs with Dynamic Data under a Bounded Slope Condition. [PDF]

open access: yesArch Ration Mech Anal
Bögelein V, Duzaar F, Treu G.
europepmc   +1 more source

Geometric Planted Matchings Beyond the Gaussian Model

open access: yesRandom Structures &Algorithms, Volume 68, Issue 4, July 2026.
ABSTRACT We consider the problem of recovering an unknown matching between a set of n$$ n $$ randomly placed points in ℝd$$ {\mathbb{R}}^d $$ and random perturbations of these points. This can be seen as a model for particle tracking and more generally, entity resolution.
Lucas R. Schwengber, Roberto I. Oliveira
wiley   +1 more source

Canonical Higher-Order Kernels for Density Derivative Estimation [PDF]

open access: yes
In this note we present r th order kernel density derivative estimators using canonical higher-order kernels. These canonical rescalings uncouple the choice of kernel and scale factor. This approach is useful for selection of the order of the kernel in a
Christopher F. Parmeter   +1 more
core  

Robust Bernoulli Mixture Models for Credit Portfolio Risk

open access: yesMathematical Finance, Volume 36, Issue 3, Page 528-543, July 2026.
ABSTRACT This paper presents comparison results and establishes risk bounds for credit portfolios within classes of Bernoulli mixture models, assuming conditionally independent defaults that are stochastically increasing in a common risk factor. We provide simple and interpretable conditions on conditional default probabilities that imply a comparison ...
Jonathan Ansari, Eva Lütkebohmert
wiley   +1 more source

Quantitative asymptotics for polynomial patterns in the primes

open access: yesMathematika, Volume 72, Issue 3, July 2026.
Abstract We prove quantitative estimates for averages of the von Mangoldt and Möbius functions along polynomial progressions n+P1(m),…,n+Pk(m)$n+P_1(m),\ldots, n+P_k(m)$ for a large class of polynomials Pi$P_i$. The error terms obtained save an arbitrary power of logarithm, matching the classical Siegel–Walfisz error term.
Lilian Matthiesen   +2 more
wiley   +1 more source

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