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A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics…

In machine learning, fewer features reduce model complexity. Carefully assessing the influence of each input feature on the model quality is therefore a crucial preprocessing step. We propose a novel feature selection algorithm based on a…

Quantum Physics · Physics 2023-02-22 Sascha Mücke , Raoul Heese , Sabine Müller , Moritz Wolter , Nico Piatkowski

Some of recent developments, including recent results, ideas, techniques, and approaches, in the study of degenerate partial differential equations are surveyed and analyzed. Several examples of nonlinear degenerate, even mixed, partial…

Analysis of PDEs · Mathematics 2015-03-17 Gui-Qiang G. Chen

Any function can be constructed using a hierarchy of simpler functions through compositions. Such a hierarchy can be characterized by a binary rooted tree. Each node of this tree is associated with a function which takes as inputs two…

Machine Learning · Computer Science 2019-10-23 Roozbeh Farhoodi , Khashayar Filom , Ilenna Simone Jones , Konrad Paul Kording

We'll measure the differences of the dual variables and the gain of the objective function when creating new problems, which each has one inequality more than the starting LP-instance. These differences of the dual variables are naturally…

Discrete Mathematics · Computer Science 2008-11-21 H. Georg Buesching

A spectral decomposition method is used to obtain solutions to a class of nonlinear differential equations. We extend this approach to the analysis of the fractional form of these equations and demonstrate the method by applying it to the…

Mathematical Physics · Physics 2015-08-14 Malgorzata Turalska , Bruce J. West

While much of the work in the design of convolutional networks over the last five years has revolved around the empirical investigation of the importance of depth, filter sizes, and number of feature channels, recent studies have shown that…

Machine Learning · Computer Science 2017-12-08 Karim Ahmed , Lorenzo Torresani

An equation containing a fractional power of an elliptic operator of second order is studied for Dirichlet boundary conditions. Finite difference approximations in space are employed. The proposed numerical algorithm is based on solving an…

Numerical Analysis · Computer Science 2015-05-18 Petr N. Vabishchevich

Whilst the partial differential equations that govern the dynamics of our world have been studied in great depth for centuries, solving them for complex, high-dimensional conditions and domains still presents an incredibly large…

Machine Learning · Computer Science 2023-03-07 Edward Small

Writing correct distributed programs is hard. In spite of extensive testing and debugging, software faults persist even in commercial grade software. Many distributed systems, especially those employed in safety-critical environments,…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Neeraj Mittal , Vijay K. Garg

We study the problem of complexity estimation in the context of parallelizing an advanced Branch and Bound-type algorithm over graphical models. The algorithm's pruning power makes load balancing, one crucial element of every distributed…

Artificial Intelligence · Computer Science 2012-10-19 Lars Otten , Rina Dechter

Quantum algorithms for both differential equation solving and for machine learning potentially offer an exponential speedup over all known classical algorithms. However, there also exist obstacles to obtaining this potential speedup in…

Quantum Physics · Physics 2022-05-03 Bobak T. Kiani , Giacomo De Palma , Dirk Englund , William Kaminsky , Milad Marvian , Seth Lloyd

The branching methods developed are effective methods to solve some semi linear PDEs and are shown numerically to be able to solve some full non linear PDEs. These methods are however restricted to some small coefficients in the PDE and…

Probability · Mathematics 2017-01-27 Xavier Warin

In this paper, we present two approximation algorithms for the directed multi-multiway cut and directed multicut problems. The so called region growing paradigm \cite{1} is modified and used for these two cut problems on directed graphs. By…

Data Structures and Algorithms · Computer Science 2020-11-06 Ramin Yarinezhad , Seyed Naser Hashemi

Cut-elimination is the bedrock of proof theory with a multitude of applications from computational interpretations to proof analysis. It is also the starting point for important meta-theoretical investigations including decidability,…

Logic in Computer Science · Computer Science 2023-05-01 Agata Ciabattoni , Timo Lang , Revantha Ramanayake

Consider an algorithm computing in a differential field with several commuting derivations such that the only operations it performs with the elements of the field are arithmetic operations, differentiation, and zero testing. We show that,…

Commutative Algebra · Mathematics 2021-08-31 Wei Li , Alexey Ovchinnikov , Gleb Pogudin , Thomas Scanlon

Identifying computational tasks suitable for (future) quantum computers is an active field of research. Here we explore utilizing quantum computers for the purpose of solving differential equations. We consider two approaches: (i) basis…

Quantum Physics · Physics 2021-07-14 Benjamin Zanger , Christian B. Mendl , Martin Schulz , Martin Schreiber

The reconstruction of the history of evolutionary genome-wide events among a set of related organisms is of great biological interest. A simplified model that captures only content modifying operations was introduced recently. It allows the…

Combinatorics · Mathematics 2012-08-15 Stefan Canzar , Sandro Andreotti

The purpose of the present article is the study of duals of functional codes on algebraic surfaces. We give a direct geometrical description of them, using differentials. Even if this geometrical description is less trivial, it can be…

Algebraic Geometry · Mathematics 2011-09-14 A. Couvreur

Many problems in Physics and Chemistry are formulated as the minimization of a functional. Therefore, methods for solving these problems typically require differentiating maps whose input and/or output are functions -- commonly referred to…

Mathematical Software · Computer Science 2024-06-25 Kangbo Li , Anil Damle
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