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We study a natural geometric variant of the classic Knapsack problem called 2D-Knapsack: we are given a set of axis-parallel rectangles and a rectangular bounding box, and the goal is to pack as many of these rectangles inside the box…

Data Structures and Algorithms · Computer Science 2023-07-21 Michal Pilipczuk , Mathieu Mari , Timothe Picavet

Mixed packing and covering problems are problems that can be formulated as linear programs using only non-negative coefficients. Examples include multicommodity network flow, the Held-Karp lower bound on TSP, fractional relaxations of set…

Data Structures and Algorithms · Computer Science 2016-01-19 Neal E. Young

We present an asymptotically faster algorithm for solving linear systems in well-structured 3-dimensional truss stiffness matrices. These linear systems arise from linear elasticity problems, and can be viewed as extensions of graph…

Data Structures and Algorithms · Computer Science 2018-05-25 Rasmus Kyng , Richard Peng , Robert Schwieterman , Peng Zhang

Vassilevska and Williams (STOC 2009) showed how to count simple paths on $k$ vertices and matchings on $k/2$ edges in an $n$-vertex graph in time $n^{k/2+O(1)}$. In the same year, two different algorithms with the same runtime were given by…

Data Structures and Algorithms · Computer Science 2015-08-17 Andreas Björklund , Petteri Kaski , Łukasz Kowalik

The problem of finding the asymptotic behavior of the maximal density of sphere packings in high Euclidean dimensions is one of the most fascinating and challenging problems in discrete geometry. One century ago, Minkowski obtained a…

Statistical Mechanics · Physics 2009-11-13 A. Scardicchio , F. H. Stillinger , S. Torquato

Low rank tensor decompositions are a powerful tool for learning generative models, and uniqueness results give them a significant advantage over matrix decomposition methods. However, tensors pose significant algorithmic challenges and…

Data Structures and Algorithms · Computer Science 2014-01-21 Aditya Bhaskara , Moses Charikar , Ankur Moitra , Aravindan Vijayaraghavan

Covering numbers are a powerful tool used in the development of approximation algorithms, randomized dimension reduction methods, smoothed complexity analysis, and others. In this paper we prove upper bounds on the covering number of…

Algebraic Geometry · Mathematics 2025-06-09 Yifan Zhang , Joe Kileel

We have formulated the problem of generating periodic dense paritcle packings as an optimization problem called the Adaptive Shrinking Cell (ASC) formulation [S. Torquato and Y. Jiao, Phys. Rev. E {\bf 80}, 041104 (2009)]. Because the…

Statistical Mechanics · Physics 2010-12-15 Sal Torquato , Yang Jiao

We develop the ultraspherical rectangular collocation (URC) method, a collocation implementation of the sparse ultraspherical method of Olver \& Townsend for two-point boundary-value problems. The URC method is provably convergent, the…

Numerical Analysis · Mathematics 2024-01-09 Thomas Trogdon

Fault tolerance is a prerequisite for scalable quantum computing. Architectures based on 2D topological codes are effective for near-term implementations of fault tolerance. To obtain high performance with these architectures, we require a…

Quantum Physics · Physics 2018-10-23 Ben Criger , Imran Ashraf

We establish dimensional thresholds for dot product sets associated with compact subsets of translated paraboloids. Specifically, we prove that when the dimension of such a subset exceeds $ \frac{5}{4} = \frac{3}{2} - \frac{1}{4} $ in…

Combinatorics · Mathematics 2025-09-16 Chun-Kai Tseng

In a previous paper it was shown that a machine learning regression problem can be solved within the framework of random function theory, with the optimal kernel analytically derived from symmetry and indifference principles and coinciding…

Machine Learning · Computer Science 2025-12-19 Yuriy N. Bakhvalov

In the numerical linear algebra community, it was suggested that to obtain nearly optimal bounds for various problems such as rank computation, finding a maximal linearly independent subset of columns (a basis), regression, or low-rank…

Data Structures and Algorithms · Computer Science 2021-11-04 Nadiia Chepurko , Kenneth L. Clarkson , Praneeth Kacham , David P. Woodruff

The pooling problem is a classical NP-hard problem in the chemical process and petroleum industries. This problem is modeled as a nonlinear, nonconvex network flow problem in which raw materials with different specifications are blended in…

Optimization and Control · Mathematics 2023-06-21 Mosayeb Jalilian , Burak Kocuk

We consider the problem of finding a low discrepancy coloring for sparse set systems where each element lies in at most t sets. We give an efficient algorithm that finds a coloring with discrepancy O((t log n)^{1/2}), matching the best…

Data Structures and Algorithms · Computer Science 2016-09-13 Nikhil Bansal , Daniel Dadush , Shashwat Garg

We study a cutting-plane method for semidefinite optimization problems (SDOs), and supply a proof of the method's convergence, under a boundedness assumption. By relating the method's rate of convergence to an initial outer approximation's…

Optimization and Control · Mathematics 2020-02-17 Dimitris Bertsimas , Ryan Cory-Wright

Designing the topology of three-dimensional structures is a challenging problem due to its memory and time consumption. In this paper, we present a robust and efficient algorithm for solving large-scale 3D topology optimization problems.…

Optimization and Control · Mathematics 2024-03-01 Alfredo Vitorino , Francisco A. M. Gomes

We consider the online carpooling problem: given $n$ vertices, a sequence of edges arrive over time. When an edge $e_t = (u_t, v_t)$ arrives at time step $t$, the algorithm must orient the edge either as $v_t \rightarrow u_t$ or $u_t…

Data Structures and Algorithms · Computer Science 2020-10-06 Anupam Gupta , Ravishankar Krishnaswamy , Amit Kumar , Sahil Singla

A well studied special case of bin packing is the 3-partition problem, where n items of size > 1/4 have to be packed in a minimum number of bins of capacity one. The famous Karmarkar-Karp algorithm transforms a fractional solution of a…

Discrete Mathematics · Computer Science 2012-02-03 Friedrich Eisenbrand , Dömötör Pálvölgyi , Thomas Rothvoß

Convergence guarantees for optimization over bounded-rank matrices are delicate to obtain because the feasible set is a non-smooth and non-convex algebraic variety. Existing techniques include projected gradient descent, fixed-rank…

Optimization and Control · Mathematics 2024-06-21 Quentin Rebjock , Nicolas Boumal