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Algorithmic stability is a classical approach to understanding and analysis of the generalization error of learning algorithms. A notable weakness of most stability-based generalization bounds is that they hold only in expectation.…

Machine Learning · Computer Science 2019-06-25 Vitaly Feldman , Jan Vondrak

We study the Subset Balancing problem: given $x \in \mathbb{Z}^n$ and a coefficient set $C \subseteq \mathbb{Z}$, find a nonzero vector $c \in C^n$ such that $c\cdot x = 0$. The standard meet-in-the-middle algorithm runs in time…

Data Structures and Algorithms · Computer Science 2026-04-27 Yiming Gao , Yansong Feng , Honggang Hu , Yanbin Pan

We give a simple proof of a well-known theorem of G\'al and of the recent related results of Aistleitner, Berkes and Seip [1] regarding the size of GCD sums. In fact, our method obtains the asymptotically sharp constant in G\'al's theorem,…

Number Theory · Mathematics 2014-08-12 Mark Lewko , Maksym Radziwill

We present an efficient parallel derandomization method for randomized algorithms that rely on concentrations such as the Chernoff bound. This settles a classic problem in parallel derandomization, which dates back to the 1980s. Consider…

Data Structures and Algorithms · Computer Science 2023-11-27 Mohsen Ghaffari , Christoph Grunau

We give a sharp lower bound to the largest possible Euclidean norm of signed sums of $n$ vectors in the plane. This is achieved by connecting the signed vector sum problem to the isoperimetric problem for the circumradius of polygons. In…

Metric Geometry · Mathematics 2025-02-20 Florian Grundbacher

Simulated DAG models may exhibit properties that, perhaps inadvertently, render their structure identifiable and unexpectedly affect structure learning algorithms. Here, we show that marginal variance tends to increase along the causal…

Machine Learning · Statistics 2021-11-11 Alexander G. Reisach , Christof Seiler , Sebastian Weichwald

Given a large data matrix $A\in\mathbb{R}^{n\times n}$, we consider the problem of determining whether its entries are i.i.d. with some known marginal distribution $A_{ij}\sim P_0$, or instead $A$ contains a principal submatrix $A_{{\sf…

Computational Complexity · Computer Science 2015-02-24 Yash Deshpande , Andrea Montanari

One of the central problems in the study of parametrized constraint satisfaction problems is the Dichotomy Conjecture by T. Feder and M. Vardi stating that the constraint satisfaction problem (CSP) over a fixed, finite constraint language…

Computational Complexity · Computer Science 2017-12-12 Dejan Delić

In this work, we study the problems of counting and sampling Mazurkiewicz traces that a regular language touches. Fix an alphabet $\Sigma$ and an independence relation $\mathbb{I} \subseteq \Sigma \times \Sigma$. The input consists of a…

Formal Languages and Automata Theory · Computer Science 2025-12-02 Alexis de Colnet , Kuldeep S. Meel , Umang Mathur

Tutte's spring embedding theorem states that, for a three-connected planar graph, if the outer face of the graph is fixed as the complement of some convex region in the plane, and all other vertices are placed at the mass center of their…

Combinatorics · Mathematics 2020-07-10 John C. Urschel , Ludmil T. Zikatanov

Marcus, Spielman and Srivastava (Annals of Mathematics 2014) solved the Kadison--Singer Problem by proving a strong form of Weaver's conjecture: they showed that for all $\alpha > 0$ and all lists of vectors of norm at most $\sqrt{\alpha}$…

Computational Complexity · Computer Science 2022-05-04 Daniel A. Spielman , Peng Zhang

One of the oldest problems in coding theory is to match the Gilbert-Varshamov bound with explicit binary codes. Over larger-yet still constant-sized-fields, algebraic-geometry codes are known to beat the GV bound. In this work, we leverage…

Information Theory · Computer Science 2025-11-13 Gil Cohen , Dean Doron , Noam Goldgraber , Tomer Manket

This paper considers various formulations of the sum-product problem. It is shown that, for a finite set $A\subset{\mathbb{R}}$, $$|A(A+A)|\gg{|A|^{\frac{3}{2}+\frac{1}{178}}},$$ giving a partial answer to a conjecture of Balog. In a…

Combinatorics · Mathematics 2014-01-09 Brendan Murphy , Oliver Roche-Newton , Ilya D. Shkredov

The $\gamma_2$-norm of Boolean matrices plays an important role in communication complexity and discrepancy theory. In this paper, we study combinatorial properties of this norm, and provide new applications, involving Zarankiewicz type…

Combinatorics · Mathematics 2025-03-04 István Tomon

Many real-world decision problems require solving, again and again, combinatorial optimization instances drawn from a common distribution. A recent line of structured learning methods exploits this regularity by learning policies that pair…

Machine Learning · Statistics 2026-05-20 Pierre-Cyril Aubin-Frankowski , Yohann De Castro , Axel Parmentier , Alessandro Rudi

The Subset Sum problem is a classical NP-complete problem with a long-standing $O^*(2^{n/2})$ deterministic bound due to Horowitz and Sahni. We present results at two distinct levels of generality. First (instance-sensitive bound), we…

Computational Complexity · Computer Science 2025-08-29 Jesus Salas

Leveraging algorithmic stability to derive sharp generalization bounds is a classic and powerful approach in learning theory. Since Vapnik and Chervonenkis [1974] first formalized the idea for analyzing SVMs, it has been utilized to study…

Machine Learning · Computer Science 2021-01-26 Qinghua Liu , Zhou Lu

The compressed indexing problem is to preprocess a string $S$ of length $n$ into a compressed representation that supports pattern matching queries. That is, given a string $P$ of length $m$ report all occurrences of $P$ in $S$. We present…

Data Structures and Algorithms · Computer Science 2018-04-12 Anders Roy Christiansen , Mikko Berggren Ettienne

The Shapley-Folkman theorem shows that Minkowski averages of uniformly bounded sets tend to be convex when the number of terms in the sum becomes much larger than the ambient dimension. In optimization, Aubin and Ekeland [1976] show that…

Optimization and Control · Mathematics 2019-07-02 Thomas Kerdreux , Igor Colin , Alexandre d'Aspremont

The simplex method for linear programming is known to be highly efficient in practice, and understanding its performance from a theoretical perspective is an active research topic. The framework of smoothed analysis, first introduced by…

Data Structures and Algorithms · Computer Science 2025-10-22 Sophie Huiberts , Yin Tat Lee , Xinzhi Zhang