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This work considers the problem of approximating initial condition and time-dependent optimal control and trajectory surfaces using multivariable Fourier series. A modified Augmented Lagrangian algorithm for translating the optimal control…

Optimization and Control · Mathematics 2023-12-14 Gabriel Nicolosi , Terry Friesz , Christopher Griffin

In this paper, we propose a column by column encoding scheme suitable for two-dimensional (2D) constraint codes and derive a lower bound of its maximum achievable rate. It is shown that the maximum achievable rate is equal to the largest…

Information Theory · Computer Science 2018-04-18 Kazuya Hirata , Tadashi Wadayama

We introduce an approximation method to solve an optimal control problem via the Lagrange dual of its weak formulation. It is based on a sum-of-squares representation of the Hamiltonian, and extends a previous method from polynomial…

Optimization and Control · Mathematics 2021-10-15 Eloïse Berthier , Justin Carpentier , Alessandro Rudi , Francis Bach

Edit distance is a fundamental measure of distance between strings and has been widely studied in computer science. While the problem of estimating edit distance has been studied extensively, the equally important question of actually…

Data Structures and Algorithms · Computer Science 2018-05-08 Moses Charikar , Ofir Geri , Michael P. Kim , William Kuszmaul

In this paper we consider two problems concerning string factorisation. Specifically given a string $w$ and an integer $k$ find a factorisation of $w$ where each factor has length bounded by $k$ and has the minimum (the FmD problem) or the…

Data Structures and Algorithms · Computer Science 2019-12-24 Angelo Monti , Blerina Sinaimeri

We consider the problem of minimizing a $d$-dimensional Lipschitz convex function using a stochastic gradient oracle. We introduce and motivate a setting where the noise of the stochastic gradient is isotropic in that it is bounded in every…

Optimization and Control · Mathematics 2025-10-24 Annie Marsden , Liam O'Carroll , Aaron Sidford , Chenyi Zhang

We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclosing balls. Our algorithms can be extended to some kernelized versions…

Machine Learning · Computer Science 2010-10-22 Kenneth L. Clarkson , Elad Hazan , David P. Woodruff

Many real life problems can be reduced to the solution of a complex exponentials approximation problem which is usually ill posed. Recently a new transform for solving this problem, formulated as a specific moments problem in the plane, has…

Numerical Analysis · Mathematics 2012-05-03 Piero Barone

We devise a projection-free iterative scheme for the approximation of harmonic maps that provides a second-order accuracy of the constraint violation and is unconditionally energy stable. A corresponding error estimate is valid under a mild…

Numerical Analysis · Mathematics 2024-05-02 Georgios Akrivis , Sören Bartels , Christian Palus

The classical pattern matching asks for locating all occurrences of one string, called the pattern, in another, called the text, where a string is simply a sequence of characters. Due to the potential practical applications, it is desirable…

Data Structures and Algorithms · Computer Science 2024-10-30 Jonas Ellert , Paweł Gawrychowski , Adam Górkiewicz , Tatiana Starikovskaya

We study the optimal transport problem for $d>2$ discrete measures. This is a linear programming problem on $d$-tensors. It gives a way to compute a "distance" between two sets of discrete measures. We introduce an entropic regularization…

Computer Vision and Pattern Recognition · Computer Science 2021-07-27 Shmuel Friedland

Conic optimization has recently emerged as a powerful tool for designing tractable and guaranteed algorithms for non-convex polynomial optimization problems. On the one hand, tractability is crucial for efficiently solving large-scale…

Some early violins have been reduced during their history to fit imposed morphological standards, while more recent ones have been built directly to these standards. We can observe differences between reduced and unreduced instruments,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Philémon Beghin , Anne-Emmanuelle Ceulemans , François Glineur

Algorithmic reproducibility measures the deviation in outputs of machine learning algorithms upon minor changes in the training process. Previous work suggests that first-order methods would need to trade-off convergence rate (gradient…

Machine Learning · Computer Science 2024-01-11 Liang Zhang , Junchi Yang , Amin Karbasi , Niao He

Variational hybrid quantum-classical optimization represents one of the most promising avenue to show the advantage of nowadays noisy intermediate-scale quantum computers in solving hard problems, such as finding the minimum-energy state of…

Quantum Physics · Physics 2020-11-18 Laura Gentini , Alessandro Cuccoli , Stefano Pirandola , Paola Verrucchi , Leonardo Banchi

Randomized dimensionality reduction is a widely-used algorithmic technique for speeding up large-scale Euclidean optimization problems. In this paper, we study dimension reduction for a variety of maximization problems, including…

Data Structures and Algorithms · Computer Science 2025-06-03 Jie Gao , Rajesh Jayaram , Benedikt Kolbe , Shay Sapir , Chris Schwiegelshohn , Sandeep Silwal , Erik Waingarten

The study of harmonic scales of musical instruments is discussed in all introductory physics texts devoted to the science of sound. In this paper, we present a new piano keyboard to make the so-called Bohlen-Pierce scale more functional and…

Popular Physics · Physics 2011-11-03 Antonio Nassar

We show that any submodular minimization (SM) problem defined on a linear constraint set with constraints having up to two variables per inequality, are 2-approximable in polynomial time. If the constraints are monotone (the two variables…

Discrete Mathematics · Computer Science 2017-05-01 Dorit S. Hochbaum

We consider optimal control problems for partial differential equations where the controls take binary values but vary over the time horizon, they can thus be seen as dynamic switches. The switching patterns may be subject to combinatorial…

Optimization and Control · Mathematics 2024-04-04 Christoph Buchheim , Alexandra Grütering , Christian Meyer

In the present paper we are concerned with a numerical algorithm for the approximation of the two-dimensional neural field equation with delay. We consider three numerical examples that have been analysed before by other authors and are…

Numerical Analysis · Mathematics 2015-11-04 Pedro M. Lima , Evelyn Buckwar