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We propose new sequential simulation-optimization algorithms for general convex optimization via simulation problems with high-dimensional discrete decision space. The performance of each choice of discrete decision variables is evaluated…

Optimization and Control · Mathematics 2022-02-15 Haixiang Zhang , Zeyu Zheng , Javad Lavaei

The Reservoir Computing (RC) paradigm posits that sufficiently complex physical systems can be used to massively simplify pattern recognition tasks and nonlinear signal prediction. This work demonstrates how random topological magnetic…

Mesoscale and Nanoscale Physics · Physics 2020-11-18 Daniele Pinna , George Bourianoff , Karin Everschor-Sitte

Many differential equations with physical backgrounds are described as gradient systems, which are evolution equations driven by the gradient of some functionals, and such problems have energy conservation or dissipation properties. For…

Numerical Analysis · Mathematics 2023-08-07 Tomoya Kemmochi

The persistence diagram (PD) is an increasingly popular topological descriptor. By encoding the size and prominence of topological features at varying scales, the PD provides important geometric and topological information about a space.…

We provide a recipe for building explicit representations of the real Clifford algebras once an explicit family is given in dimensions $1$ through $4$. We further give an explicit construction of spin coordinate systems for a given real…

Differential Geometry · Mathematics 2025-05-23 Jesus Sanchez

Intelligent reflecting surface (IRS) has emerged as a promising solution to enhance wireless information transmissions by adaptively controlling prorogation environment. Recently, the brand-new concept of utilizing IRS to implement a…

Signal Processing · Electrical Eng. & Systems 2021-03-23 Rang Liu , Hongyu Li , Ming Li , Qian Liu

Due to the highly non-convex nature of large-scale robust parameter estimation, avoiding poor local minima is challenging in real-world applications where input data is contaminated by a large or unknown fraction of outliers. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2020-03-23 Huu Le , Christopher Zach

Solving optimization tasks based on functions and losses with a topological flavor is a very active, growing field of research in data science and Topological Data Analysis, with applications in non-convex optimization, statistics and…

Computational Geometry · Computer Science 2021-02-19 Mathieu Carrière , Frédéric Chazal , Marc Glisse , Yuichi Ike , Hariprasad Kannan

Constructing 3D representations of object geometry is critical for many robotics tasks, particularly manipulation problems. These representations must be built from potentially noisy partial observations. In this work, we focus on the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Herbert Wright , Weiming Zhi , Martin Matak , Matthew Johnson-Roberson , Tucker Hermans

We describe a method to obtain spherical parameterizations of arbitrary data through the use of persistent cohomology and variational optimization. We begin by computing the second-degree persistent cohomology of the filtered Vietoris-Rips…

Algebraic Topology · Mathematics 2025-03-11 Nikolas C. Schonsheck , Stefan C. Schonsheck

A simple and efficient algorithm to numerically compute the genus of surfaces of three-dimensional objects using the Euler characteristic formula is presented. The algorithm applies to objects obtained by thresholding a scalar field in a…

Fluid Dynamics · Physics 2017-09-05 Adrián Lozano-Durán , Guillem Borrell

An explicit numerical strategy that practically preserves invariants is derived for conservative systems by combining an explicit high-order Runge-Kutta (RK) scheme with a simple modification of the standard projection approach, which is…

Numerical Analysis · Mathematics 2020-09-16 Wenjun Cai , Yuezheng Gong , Yushun Wang

Incremental learning aims to enable machine learning models to continuously acquire new knowledge given new classes, while maintaining the knowledge already learned for old classes. Saving a subset of training samples of previously seen…

Computer Vision and Pattern Recognition · Computer Science 2021-04-22 Jian Jiang , Edoardo Cetin , Oya Celiktutan

This paper presents a computational framework for the concise encoding of an ensemble of persistence diagrams, in the form of weighted Wasserstein barycenters [100], [102] of a dictionary of atom diagrams. We introduce a multi-scale…

Machine Learning · Computer Science 2023-09-18 Keanu Sisouk , Julie Delon , Julien Tierny

A computational framework based on nonlinear direct-adjoint looping is presented for optimizing mixing strategies for binary fluid systems. The governing equations are the nonlinear Navier-Stokes equations, augmented by an evolution…

Fluid Dynamics · Physics 2020-01-27 Maximilian F. Eggl , Peter J. Schmid

Morse decompositions partition the flows in a vector field into equivalent structures. Given such a decomposition, one can define a further summary of its flow structure by what is called a connection matrix.These matrices, a generalization…

Dynamical Systems · Mathematics 2025-07-31 Tamal K. Dey , Michał Lipiński , Andrew Haas

Identifying spurious reduction artefacts in galaxy spectra is a challenge for large surveys. We present an algorithm for identifying and repairing residual spurious features in sky-subtracted galaxy spectra with application to the VIPERS…

A tower is a sequence of simplicial complexes connected by simplicial maps. We show how to compute a filtration, a sequence of nested simplicial complexes, with the same persistent barcode as the tower. Our approach is based on the coning…

Algebraic Topology · Mathematics 2017-10-13 Michael Kerber , Hannah Schreiber

Registers are the fastest memory components within the GPU's complex memory hierarchy, accessed by names rather than addresses. They are managed entirely by the compiler through a process called register allocation, during which the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-28 Deniz Elbek , Kamer Kaya

Automatic segmentation of an image to identify all meaningful parts is one of the most challenging as well as useful tasks in a number of application areas. This is widely studied. Selective segmentation, less studied, aims to use limited…

Numerical Analysis · Mathematics 2019-07-08 Michael Roberts , Ke Chen , Klaus L. Irion