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Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration…

Optimization and Control · Mathematics 2019-01-25 Ching-pei Lee , Stephen J. Wright

A cumbersome operation in numerical analysis and linear algebra, optimization, machine learning and engineering algorithms; is inverting large full-rank matrices which appears in various processes and applications. This has both numerical…

Numerical Analysis · Mathematics 2022-06-24 Neophytos Charalambides , Mert Pilanci , Alfred O. Hero

Given a graph, the sparsest cut problem asks for a subset of vertices whose edge expansion (the normalized cut given by the subset) is minimized. In this paper, we study a generalization of this problem seeking for $ k $ disjoint subsets of…

Data Structures and Algorithms · Computer Science 2017-02-21 Ramin Javadi , Saleh Ashkboos

Motion planning problems have been studied by both the robotics and the controls research communities for a long time, and many algorithms have been developed for their solution. Among them, incremental sampling-based motion planning…

Robotics · Computer Science 2012-05-01 Oktay Arslan , Panagiotis Tsiotras

The development of a satisfying and rigorous mathematical understanding of the performance of neural networks is a major challenge in artificial intelligence. Against this background, we study the expressive power of neural networks through…

Machine Learning · Computer Science 2024-07-12 Christoph Hertrich , Martin Skutella

An important goal in algorithm design is determining the best running time for solving a problem (approximately). For some problems, we know the optimal running time, assuming certain conditional lower bounds. In this work, we study the…

Data Structures and Algorithms · Computer Science 2024-03-04 Moritz Buchem , Paul Deuker , Andreas Wiese

The integration of constrained optimization models as components in deep networks has led to promising advances on many specialized learning tasks. A central challenge in this setting is backpropagation through the solution of an…

Machine Learning · Computer Science 2024-01-01 James Kotary , Jacob Christopher , My H Dinh , Ferdinando Fioretto

In the Minimum Clique Routing Problem on Cycles \textsc{MCRPC} we are given a cycle together with a set of demands (weighted origin-destination pairs) and the goal is to route all the pairs minimizing the maximum weighted clique of the…

Data Structures and Algorithms · Computer Science 2023-11-17 Mariana Escalante , Martín Matamala , Iván Rapaport , Paola Tolomei , Luis Miguel Torres

We introduce a computational origami problem which we call the segment folding problem: given a set of $n$ line-segments in the plane the aim is to make creases along all segments in the minimum number of folding steps. Note that a folding…

Computational Geometry · Computer Science 2022-01-17 Takashi Horiyama , Fabian Klute , Matias Korman , Irene Parada , Ryuhei Uehara , Katsuhisa Yamanaka

This paper presents constant-time and near-constant-time distributed algorithms for a variety of problems in the congested clique model. We show how to compute a 3-ruling set in expected $O(\log \log \log n)$ rounds and using this, we…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-12 James W. Hegeman , Sriram V. Pemmaraju , Vivek B. Sardeshmukh

We study numerical integration of smooth functions defined over the $s$-dimensional unit cube. A recent work by Dick et al. (2019) has introduced so-called extrapolated polynomial lattice rules, which achieve the almost optimal rate of…

Numerical Analysis · Mathematics 2020-07-15 Takashi Goda

Cranley and Patterson put forward the following randomization as the basis for the estimation of the error of a lattice rule for an integral of a one-periodic function over the unit cube in s dimensions. The lattice rule is randomized using…

Computation · Statistics 2014-06-03 Paul Kabaila

Given real numbers whose sum is an integer, we study the problem of finding integers which match these real numbers as closely as possible, in the sense of L^p norm, while preserving the sum. We describe the structure of solutions for this…

Data Structures and Algorithms · Computer Science 2015-01-05 Rama Cont , Massoud Heidari

Coherent quantum rollout for sequential decision problems requires a unitary simulator: randomness must live in explicit quantum registers, and basis-state selectors must be mapped to actions reversibly. With branch-dependent valid actions,…

Quantum Physics · Physics 2026-04-30 Nishant Shukla

Rollout algorithms have demonstrated excellent performance on a variety of dynamic and discrete optimization problems. Interpreted as an approximate dynamic programming algorithm, a rollout algorithm estimates the value-to-go at each…

Data Structures and Algorithms · Computer Science 2013-11-27 Andrew Mastin , Patrick Jaillet

Positive linear programs (LP), also known as packing and covering linear programs, are an important class of problems that bridges computer science, operations research, and optimization. Despite the consistent efforts on this problem, all…

Data Structures and Algorithms · Computer Science 2016-11-15 Zeyuan Allen-Zhu , Lorenzo Orecchia

The problem that we consider is the following: given an $n \times n$ array $A$ of positive numbers, find a tiling using at most $p$ rectangles (which means that each array element must be covered by some rectangle and no two rectangles must…

Data Structures and Algorithms · Computer Science 2017-03-07 Grzegorz Głuch , Krzysztof Loryś

The Subset Sum Problem is a fundamental NP-complete problem in cryptography and combinatorial optimization, with many real-world applications. The Random Subset Sum Problem (RSSP) is a more applicable version of subset sum, where numbers…

Data Structures and Algorithms · Computer Science 2026-05-21 Edwin Chen , Christof Teuscher

We first present a simple recursive algorithm that generates cyclic rotation Gray codes for stamp foldings and semi-meanders, where consecutive strings differ by a stamp rotation. These are the first known Gray codes for stamp foldings and…

Data Structures and Algorithms · Computer Science 2024-11-11 Bowie Liu , Dennis Wong , Chan-Tong Lam , Marcus Im

It is common to encounter situations where one must solve a sequence of similar computational problems. Running a standard algorithm with worst-case runtime guarantees on each instance will fail to take advantage of valuable structure…

Machine Learning · Computer Science 2019-04-29 Daniel Alabi , Adam Tauman Kalai , Katrina Ligett , Cameron Musco , Christos Tzamos , Ellen Vitercik