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We introduce a functional gradient descent trajectory optimization algorithm for robot motion planning in Reproducing Kernel Hilbert Spaces (RKHSs). Functional gradient algorithms are a popular choice for motion planning in complex…

Robotics · Computer Science 2016-01-15 Zita Marinho , Anca Dragan , Arun Byravan , Byron Boots , Siddhartha Srinivasa , Geoffrey Gordon

We consider the EBT algorithm (a particle method) for the non-local equation with a discontinuous interaction kernel. The main difficulty lies in the low regularity of the kernel which is not Lipschitz continuous, thus preventing the…

Numerical Analysis · Mathematics 2021-06-23 Piotr Gwiazda , Błażej Miasojedow , Jakub Skrzeczkowski , Zuzanna Szymańska

We exhibit differential geometric structures that arise in numerical methods, based on the construction of Cauchy sequences, that are currently used to prove explicitly the existence of weak solutions to functional equations. We describe…

Functional Analysis · Mathematics 2020-08-13 Jean-Pierre Magnot

We consider decompositions of digraphs into edge-disjoint paths and describe their connection with the $n$-th Weyl algebra of differential operators. This approach gives a graph-theoretic combinatorial view of the normal ordering problem…

Combinatorics · Mathematics 2015-03-26 Askar Dzhumadil'daev , Damir Yeliussizov

We explore the application of automated reasoning techniques to unknot detection, a classical problem of computational topology. We adopt a two-pronged experimental approach, using a theorem prover to try to establish a positive result…

Logic in Computer Science · Computer Science 2014-05-19 Andrew Fish , Alexei Lisitsa

Linear rankwidth is a linearized variant of rankwidth, introduced by Oum and Seymour [Approximating clique-width and branch-width. J. Combin. Theory Ser. B, 96(4):514--528, 2006]. Motivated from recent development on graph modification…

Data Structures and Algorithms · Computer Science 2016-01-13 Mamadou Moustapha Kanté , Eun Jung Kim , O-joung Kwon , Christophe Paul

We enumerate the number of monotonic lattice paths starting at $(0,0)$ and terminating at $(m,n)$ in which $l$ of the first $k$ steps lie below the line $y=x\ (0\leq k\leq m\leq n)$. These closed formulas consist of terms which are a…

Combinatorics · Mathematics 2015-08-21 Charles Hoffman , Corey Manack

In this article we investigate the lattices of Dyck paths of type $A$ and $B$ under dominance order, and explicitly describe their Heyting algebra structure. This means that each Dyck path of either type has a relative pseudocomplement with…

Combinatorics · Mathematics 2017-08-08 Henri Mühle

We introduce the sub-lattice approach, a procedure to generate, from a given integrable lattice, a sub-lattice which inherits its integrability features. We consider, as illustrative example of this approach, the discrete Moutard 4-point…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. Doliwa , P. Grinevich , M. Nieszporski , P. M. Santini

We describe rational knots with any of the possible combinations of the properties (a)chirality, (non-)positivity, (non-)fiberedness, and unknotting number one (or higher), and determine exactly their number for a given number of crossings…

Geometric Topology · Mathematics 2016-09-07 A. Stoimenow

Graph-structured data arise ubiquitously in many application domains. A fundamental problem is to quantify their similarities. Graph kernels are often used for this purpose, which decompose graphs into substructures and compare these…

Machine Learning · Computer Science 2020-03-26 Wei Ye , Zhen Wang , Rachel Redberg , Ambuj Singh

By leveraging the kernel trick in the output space, kernel-induced losses provide a principled way to define structured output prediction tasks for a wide variety of output modalities. In particular, they have been successfully used in the…

Machine Learning · Statistics 2024-06-14 Tamim El Ahmad , Junjie Yang , Pierre Laforgue , Florence d'Alché-Buc

Kernel methods are fundamental tools in machine learning that allow detection of non-linear dependencies between data without explicitly constructing feature vectors in high dimensional spaces. A major disadvantage of kernel methods is…

Data Structures and Algorithms · Computer Science 2020-12-23 Thomas D. Ahle , Michael Kapralov , Jakob B. T. Knudsen , Rasmus Pagh , Ameya Velingker , David Woodruff , Amir Zandieh

We present two classes of random walks restricted to the quarter plane whose generating function is not holonomic. The non-holonomy is established using the iterated kernel method, a recent variant of the kernel method. This adds evidence…

Combinatorics · Mathematics 2011-02-10 Marni Mishna , Andrew Rechnitzer

We investigate the asymptotic behavior of random paths on a graded graph which describes the subword order for words in two letters. This graph, denoted by $\mathcal{Z}$, has been introduced by Viennot, who also discovered a remarkable…

Probability · Mathematics 2018-09-24 Pierre Tarrago

We propose a discrete lattice version of the Fokker-Planck kinetic equation along lines similar to the Lattice-Boltzmann scheme. Our work extends an earlier one-dimensional formulation to arbitrary spatial dimension $D$. A generalized…

Statistical Mechanics · Physics 2009-11-11 Daniele Moroni , Benjamin Rotenberg , Jean-Pierre Hansen , Sauro Succi , Simone Melchionna

This dissertation explores applications of discrete geometry in mathematical neuroscience. We begin with convex neural codes, which model the activity of hippocampal place cells and other neurons with convex receptive fields. In Chapter 4,…

Neurons and Cognition · Quantitative Biology 2022-09-19 Caitlin Lienkaemper

Let k be a global field and let k_v be the completion of k with respect to v, a non-archimedean place of k. Let \mathbf{G} be a connected, simply-connected algebraic group over k, which is absolutely almost simple of k_v-rank 1. Let…

Group Theory · Mathematics 2007-10-23 A. W. Mason , A. Premet , B. Sury , P. A. Zalesskii

We study a class of observables in four-dimensional superconformal Yang--Mills theories which, in the planar limit at finite 't Hooft coupling, can be expressed as determinants of semi-infinite matrices built from Bessel functions. This…

High Energy Physics - Theory · Physics 2025-08-29 G. P. Korchemsky

The paper presents an approach to derive finite genus solutions to the lattice potential Kadomtsev-Petviashvili (lpKP) equation introduced by F.W. Nijhoff, et al. This equation is rederived from compatible conditions of three replicas of…

Exactly Solvable and Integrable Systems · Physics 2020-07-10 Cewen Cao , Xiaoxue Xu , Da-jun Zhang
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