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Measuring the vibronic spectrum probes dynamical processes in molecular systems. When interpreted via suitable theoretical tools, the experimental data provides comprehensive information about the system in question. For complex many-body…

Chemical Physics · Physics 2018-12-05 Sven Karsten , Sergei D. Ivanov , Sergey I. Bokarev , Oliver Kühn

A highly influential ingredient of many techniques designed to exploit sparsity in numerical optimization is the so-called chordal extension of a graph representation of the optimization problem. The definitive relation between chordal…

Machine Learning · Computer Science 2019-10-18 Defeng Liu , Andrea Lodi , Mathieu Tanneau

Digital processing-in-memory (PIM) architectures are rapidly emerging to overcome the memory-wall bottleneck by integrating logic within memory elements. Such architectures provide vast computational power within the memory itself in the…

Hardware Architecture · Computer Science 2023-04-18 Orian Leitersdorf , Dean Leitersdorf , Jonathan Gal , Mor Dahan , Ronny Ronen , Shahar Kvatinsky

Conic optimization plays a crucial role in many machine learning (ML) problems. However, practical algorithms for conic constrained ML problems with large datasets are often limited to specific use cases, as stochastic algorithms for…

Optimization and Control · Mathematics 2025-11-11 Chuan He , Zhanwang Deng

Indefinite quadratic programs (QPs) are known to be very difficult to be solved to global optimality, so are linear programs with linear complementarity constraints. Treating the former as a subclass of the latter, this paper presents a…

Optimization and Control · Mathematics 2025-03-18 Xinyao Zhang , Shaoning Han , Jong-Shi Pang

Aligning partially overlapping point sets where there is no prior information about the value of the transformation is a challenging problem in computer vision. To achieve this goal, we first reduce the objective of the robust point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-07 Wei Lian , WangMeng Zuo , Lei Zhang

Geometric numerical integration has recently been exploited to design symplectic accelerated optimization algorithms by simulating the Lagrangian and Hamiltonian systems from the variational framework introduced in Wibisono et al. In this…

Optimization and Control · Mathematics 2023-05-19 Valentin Duruisseaux , Melvin Leok

This paper tackles the challenging problem of jointly inferring time-varying network topologies and imputing missing data from partially observed graph signals. We propose a unified non-convex optimization framework to simultaneously…

Machine Learning · Statistics 2026-05-07 Chuansen Peng , Xiaojing Shen

Polytopal methods provide a flexible framework for the numerical approximation of partial differential equations on general meshes. Their convergence analysis raises specific challenges due to their inherently non-conforming nature and, in…

Numerical Analysis · Mathematics 2026-05-25 Lourenço Beirão da Veiga , Daniele Antonio Di Pietro , Jérôme Droniou

Measurement data is often sampled irregularly i.e. not on equidistant time grids. This is also true for Hamiltonian systems. However, existing machine learning methods, which learn symplectic integrators, such as SympNets [20] and…

Machine Learning · Computer Science 2025-09-22 Konrad Janik , Peter Benner

Hamiltonian systems are differential equations which describe systems in classical mechanics, plasma physics, and sampling problems. They exhibit many structural properties, such as a lack of attractors and the presence of conservation…

Numerical Analysis · Mathematics 2022-01-14 Christian Offen , Sina Ober-Blöbaum

Processing-in-memory (PIM) promises to alleviate the data movement bottleneck in modern computing systems. However, current real-world PIM systems have the inherent disadvantage that their hardware is more constrained than in conventional…

Mathematical Software · Computer Science 2023-09-07 Maurus Item , Juan Gómez-Luna , Yuxin Guo , Geraldo F. Oliveira , Mohammad Sadrosadati , Onur Mutlu

We propose HAMSI (Hessian Approximated Multiple Subsets Iteration), which is a provably convergent, second order incremental algorithm for solving large-scale partially separable optimization problems. The algorithm is based on a local…

We construct a structure preserving non-conforming finite element approximation scheme for the bi-harmonic wave maps into spheres equation. It satisfies a discrete energy law and preserves the non-convex sphere constraint of the continuous…

Numerical Analysis · Mathematics 2026-04-09 Ľubomír Baňas , Sebastian Herr

This paper proposes a projection-based implicit modeling method (PIMM) for functionally graded lattice optimization, which does not require any homogenization techniques. In this method, a parametric projection function is proposed to link…

Computational Physics · Physics 2020-08-18 Hao Deng , Albert C. To

The recent development of spectral method has been praised for its high-order convergence in simulating complex physical problems. The combination of embedded boundary method and spectral method becomes a mainstream way to tackle…

Numerical Analysis · Mathematics 2018-03-08 Po-Yi Wu , Cheng-Hong Robert Kao , Tony Wen-Hann Sheu

This paper is concerned with the variational inequality problem (VIP) over the fixed point set of a quasi-nonexpansive operator. We propose, in particular, an algorithm which entails, at each step, projecting onto a suitably chosen…

Optimization and Control · Mathematics 2013-04-03 Andrzej Cegielski , Aviv Gibali , Simeon Reich , Rafał Zalas

In this paper, a novel parallel hybrid iterative method is proposed for finding a common element of the set of solutions of a system of equilibrium problems, the set of solutions of variational inequalities for inverse strongly monotone…

Optimization and Control · Mathematics 2015-10-28 Dang Van Hieu

This paper presents a geometric approach to pitch estimation (PE)-an important problem in Music Information Retrieval (MIR), and a precursor to a variety of other problems in the field. Though there exist a number of highly-accurate…

Sound · Computer Science 2020-12-09 Tom Goodman , Karoline van Gemst , Peter Tino

In this paper, we consider an optimal control problem of an ordinary differential inclusion governed by the hypergraph Laplacian, which is defined as a subdifferential of a convex function and then is a set-valued operator. We can assure…

Optimization and Control · Mathematics 2024-09-04 Takeshi Fukao , Masahiro Ikeda , Shun Uchida
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