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This work presents a novel algorithm for progressively adapting neural network architecture along the depth. In particular, we attempt to address the following questions in a mathematically principled way: i) Where to add a new capacity…

Machine Learning · Computer Science 2026-03-03 C G Krishnanunni , Tan Bui-Thanh , Clint Dawson

Online ride-hailing platforms aim to deliver efficient mobility-on-demand services, often facing challenges in balancing dynamic and spatially heterogeneous supply and demand. Existing methods typically fall into two categories:…

Artificial Intelligence · Computer Science 2025-10-28 Yi Zhang , Yushen Long , Yun Ni , Liping Huang , Xiaohong Wang , Jun Liu

We study the feature-based newsvendor problem, in which a decision-maker has access to historical data consisting of demand observations and exogenous features. In this setting, we investigate feature selection, aiming to derive sparse,…

Machine Learning · Computer Science 2022-09-13 Breno Serrano , Stefan Minner , Maximilian Schiffer , Thibaut Vidal

In the reduced order modeling (ROM) framework, the solution of a parametric partial differential equation is approximated by combining the high-fidelity solutions of the problem at hand for several properly chosen configurations. Examples…

Numerical Analysis · Mathematics 2019-05-16 Nicola Demo , Marco Tezzele , Andrea Mola , Gianluigi Rozza

We present a gradient-based identification algorithm to identify the system matrices of a linear port-Hamiltonian system from given input-output time data. Aiming for a direct structure-preserving approach, we employ techniques from optimal…

Optimization and Control · Mathematics 2023-12-22 Michael Günther , Birgit Jacob , Claudia Totzeck

This paper considers the design of structures made of engineered materials, accounting for uncertainty in material properties. We present a topology optimization approach that optimizes the structural shape and topology at the macroscale…

Optimization and Control · Mathematics 2021-10-27 Subhayan De , Kurt Maute , Alireza Doostan

This paper introduces a multi-level (m-lev) mechanism into Evolution Strategies (ESs) in order to address a class of global optimization problems that could benefit from fine discretization of their decision variables. Such problems arise…

Neural and Evolutionary Computing · Computer Science 2020-10-06 Ofer M. Shir , Xi Xing , Herschel Rabitz

We propose a new method to design adaptation algorithms that guarantee a certain prescribed level of performance and are applicable to systems with nonconvex parameterization. The main idea behind the method is, given the desired…

Optimization and Control · Mathematics 2007-05-23 I. Y. Tyukin , D. V. Prokhorov , Cees van Leeuwen

Most biological tissues grow by the synthesis of new material close to the tissue's interface, where spatial interactions can exert strong geometric influences on the local rate of growth. These geometric influences may be mechanistic, or…

Numerical Analysis · Mathematics 2020-05-28 Mohd Almie Alias , Pascal R Buenzli

In this contribution, a finite element scheme to impose mixed boundary conditions without introducing Lagrange multipliers is presented for hyperbolic systems described as port-Hamiltonian systems. The strategy relies on finite element…

Numerical Analysis · Mathematics 2026-01-23 S. D. M. de Jong , A. Brugnoli , R. Rashad , Y. Zhang , S. Stramigioli

In this paper, we present a novel tolerance allocation algorithm for the assessment and control of geometric variation on system performance that is applicable to any system of partial differential equations. In particular, we parameterize…

Numerical Analysis · Mathematics 2019-04-16 Joseph Benzaken , Alireza Doostan , John A. Evans

We present a new high order finite element method for the discretization of partial differential equations on stationary smooth surfaces which are implicitly described as the zero level of a level set function. The discretization is based…

Numerical Analysis · Mathematics 2017-04-17 Jörg Grande , Christoph Lehrenfeld , Arnold Reusken

We present a new finite element method, called $\phi$-FEM, to solve numerically elliptic partial differential equations with natural (Neumann or Robin) boundary conditions using simple computational grids, not fitted to the boundary of the…

Numerical Analysis · Mathematics 2020-12-08 Michel Duprez , Vanessa Lleras , Alexei Lozinski

In this paper, we propose a multilevel stochastic framework for the solution of nonconvex unconstrained optimization problems. The proposed approach uses random regularized first-order models that exploit an available hierarchical…

Optimization and Control · Mathematics 2025-11-27 Filippo Marini , Margherita Porcelli , Elisa Riccietti

Recent efforts to accelerate first-order methods have focused on convex optimization problems that satisfy a geometric property known as error-bound condition, which covers a broad class of problems, including piece-wise linear programs and…

Optimization and Control · Mathematics 2025-10-16 Qihang Lin , Negar Soheili , Runchao Ma , Selvaprabu Nadarajah

In this paper we propose a high-order accurate scheme for image segmentation based on the level-set method. In this approach, the curve evolution is described as the 0-level set of a representation function but we modify the velocity that…

Numerical Analysis · Mathematics 2020-01-08 Maurizio Falcone , Giulio Paolucci , Silvia Tozza

We propose a method to modify a polygonal mesh in order to fit the zero-isoline of a level set function by extending a standard body-fitted strategy to a tessellation with arbitrarily-shaped elements. The novel level set-fitted approach, in…

Computational Engineering, Finance, and Science · Computer Science 2023-11-03 Nicola Ferro , Stefano Micheletti , Nicola Parolini , Simona Perotto , Marco Verani , Paola Francesca Antonietti

Topology optimization of frame structures under free-vibration eigenvalue constraints constitutes a challenging nonconvex polynomial optimization problem with disconnected feasible sets. In this article, we first formulate it as a…

Optimization and Control · Mathematics 2025-09-08 Marek Tyburec , Michal Kočvara , Marouan Handa , Jan Zeman

Evolutionary algorithms serve as a powerful paradigm for tackling optimization challenges, yet their reliance on manually engineered heuristics inherently limits their adaptability across diverse landscapes. However, the transition from the…

Neural and Evolutionary Computing · Computer Science 2026-03-04 Jiaxin Gao , Yaohua Liu , Ran Cheng , Kay Chen Tan

Topological states of fermionic matter can be induced by means of a suitably engineered dissipative dynamics. Dissipation then does not occur as a perturbation, but rather as the main resource for many-body dynamics, providing a targeted…

Quantum Physics · Physics 2015-06-15 C. -E. Bardyn , M. A. Baranov , C. V. Kraus , E. Rico , A. Imamoglu , P. Zoller , S. Diehl
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