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We prove several hardness results for training depth-2 neural networks with the ReLU activation function; these networks are simply weighted sums (that may include negative coefficients) of ReLUs. Our goal is to output a depth-2 neural…

Machine Learning · Computer Science 2020-11-30 Surbhi Goel , Adam Klivans , Pasin Manurangsi , Daniel Reichman

In the context of fine-grained complexity, we investigate the notion of certificate enabling faster polynomial-time algorithms. We specifically target radius (minimum eccentricity), diameter (maximum eccentricity), and all-eccentricity…

Discrete Mathematics · Computer Science 2026-01-26 Feodor F. Dragan , Guillaume Ducoffe , Michel Habib , Laurent Viennot

We consider the clustering aggregation problem in which we are given a set of clusterings and want to find an aggregated clustering which minimizes the sum of mismatches to the input clusterings. In the binary case (each clustering is a…

Computational Complexity · Computer Science 2023-11-10 Jiehua Chen , Danny Hermelin , Manuel Sorge

In this note, we propose a framework for proving computational lower bounds in norm approximation by leveraging a reverse detection--estimation gap. The starting point is a testing problem together with an estimator whose error is…

Statistics Theory · Mathematics 2026-04-07 Runshi Tang , Yuefeng Han , Anru R. Zhang

Large time-varying graphs are increasingly common in financial, social and biological settings. Feature extraction that efficiently encodes the complex structure of sparse, multi-layered, dynamic graphs presents computational and…

Machine Learning · Computer Science 2023-05-12 Umar Islambekov , Hasani Pathirana , Omid Khormali , Cuneyt Akcora , Ekaterina Smirnova

This paper presents the following results on sets that are complete for NP. 1. If there is a problem in NP that requires exponential time at almost all lengths, then every many-one NP-complete set is complete under length-increasing…

Computational Complexity · Computer Science 2010-02-03 Xiaoyang Gu , John M. Hitchcock , A. Pavan

We show tight lower bounds for the entire trade-off between space and query time for the Approximate Near Neighbor search problem. Our lower bounds hold in a restricted model of computation, which captures all hashing-based approaches. In…

Data Structures and Algorithms · Computer Science 2016-08-22 Alexandr Andoni , Thijs Laarhoven , Ilya Razenshteyn , Erik Waingarten

Computing the Euler genus of a graph is a fundamental problem in graph theory and topology. It has been shown to be NP-hard by [Thomassen '89] and a linear-time fixed-parameter algorithm has been obtained by [Mohar '99]. Despite extensive…

Data Structures and Algorithms · Computer Science 2014-12-05 Ken-ichi Kawarabayashi , Anastasios Sidiropoulos

In the recent years, intensive research work has been dedicated to prove conditional lower bounds in order to reveal the inner structure of the class P. These conditional lower bounds are based on many popular conjectures on well-studied…

Data Structures and Algorithms · Computer Science 2017-10-04 Isaac Goldstein , Moshe Lewenstein , Ely Porat

We describe a general purpose algorithm for counting simple cycles and simple paths of any length $\ell$ on a (weighted di)graph on $N$ vertices and $M$ edges, achieving a time complexity of $O\left(N+M+\big(\ell^\omega+\ell\Delta\big)…

Data Structures and Algorithms · Computer Science 2019-09-12 Pierre-Louis Giscard , Nils Kriege , Richard C. Wilson

Given an $n*n$ sparse symmetric matrix with $m$ nonzero entries, performing Gaussian elimination may turn some zeroes into nonzero values. To maintain the matrix sparse, we would like to minimize the number $k$ of these changes, hence…

Computational Complexity · Computer Science 2016-06-28 Yixin Cao , R. B. Sandeep

We propose a general framework for solving forward and inverse problems constrained by partial differential equations, where we interpolate neural networks onto finite element spaces to represent the (partial) unknowns. The framework…

Numerical Analysis · Mathematics 2023-10-11 Santiago Badia , Wei Li , Alberto F. Martín

The $3$SUM hypothesis, the APSP hypothesis and SETH are the three main hypotheses in fine-grained complexity. So far, within the area, the first two hypotheses have mainly been about integer inputs in the Word RAM model of computation. The…

Computational Complexity · Computer Science 2022-04-15 Timothy M. Chan , Virginia Vassilevska Williams , Yinzhan Xu

Topological invariants of a dataset, such as the number of holes that survive from one length scale to another (persistent Betti numbers) can be used to analyze and classify data in machine learning applications. We present an improved…

Quantum Physics · Physics 2026-04-15 Sam McArdle , András Gilyén , Mario Berta

$ \newcommand{\problem}[1]{\ensuremath{\mathrm{#1}} } \newcommand{\SVP}{\problem{SVP}} \newcommand{\ensuremath}[1]{#1} $We prove the following quantitative hardness results for the Shortest Vector Problem in the $\ell_p$ norm ($\SVP_p$),…

Computational Complexity · Computer Science 2019-01-23 Divesh Aggarwal , Noah Stephens-Davidowitz

For elliptic systems with block structure in the upper half-space and t-independent coefficients, we settle the study of boundary value problems by proving compatible well-posedness of Dirichlet, regularity and Neumann problems in optimal…

Analysis of PDEs · Mathematics 2024-04-04 Pascal Auscher , Moritz Egert

This paper proposes a novel variant of hyperinterpolation, called hard thresholding hyperinterpolation. This approximation scheme of degree $n$ leverages a hard thresholding operator to filter all hyperinterpolation coefficients, which…

Numerical Analysis · Mathematics 2024-11-28 Congpei An , Jiashu Ran

M.Alekhnovich et al. recently have proposed a model of algorithms, called BT model, which covers Greedy, Backtrack and Simple Dynamic Programming methods and can be further divided into fixed, adaptive and fully adaptive three kinds, and…

Computational Complexity · Computer Science 2007-05-23 Xin Li , Tian Liu , Han Peng , Hongtao Sun , Jiaqi Zhu

This paper is concerned with the hard thresholding operator which sets all but the $k$ largest absolute elements of a vector to zero. We establish a {\em tight} bound to quantitatively characterize the deviation of the thresholded solution…

Machine Learning · Statistics 2020-08-12 Jie Shen , Ping Li

The \emph{Dominating $H$-Pattern} problem generalizes the classical $k$-Dominating Set problem: for a fixed \emph{pattern} $H$ and a given graph $G$, the goal is to find an induced subgraph $S$ of $G$ such that (1) $S$ is isomorphic to $H$,…

Data Structures and Algorithms · Computer Science 2025-10-15 Jonathan Dransfeld , Marvin Künnemann , Mirza Redzic , Marcus Wunderlich
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