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In the restricted shortest paths problem, we are given a graph $G$ whose edges are assigned two non-negative weights: lengths and delays, a source $s$, and a delay threshold $D$. The goal is to find, for each target $t$, the length of the…

Data Structures and Algorithms · Computer Science 2024-10-23 Vikrant Ashvinkumar , Aaron Bernstein , Adam Karczmarz

In this paper, assuming the low-degree conjecture, we provide evidence of computational hardness for two problems: (1) the (partial) matching recovery problem in the sparse correlated Erd\H{o}s-R\'enyi graphs $\mathcal G(n,q;\rho)$ when the…

Machine Learning · Statistics 2025-12-30 Zhangsong Li

Given a directed, weighted graph $G=(V,E)$ undergoing edge insertions, the incremental single-source shortest paths (SSSP) problem asks for the maintenance of approximate distances from a dedicated source $s$ while optimizing the total time…

Data Structures and Algorithms · Computer Science 2021-10-25 Rasmus Kyng , Simon Meierhans , Maximilian Probst Gutenberg

The Small Set Expansion Hypothesis (SSEH) is a conjecture which roughly states that it is NP-hard to distinguish between a graph with a small subset of vertices whose edge expansion is almost zero and one in which all small subsets of…

Computational Complexity · Computer Science 2017-05-11 Pasin Manurangsi

We present efficient counting and sampling algorithms for random $k$-SAT when the clause density satisfies $\alpha \le \frac{2^k}{\mathrm{poly}(k)}.$ In particular, the exponential term $2^k$ matches the satisfiability threshold…

Data Structures and Algorithms · Computer Science 2024-11-06 Zongchen Chen , Aditya Lonkar , Chunyang Wang , Kuan Yang , Yitong Yin

We consider a variation of the spectral sparsification problem where we are required to keep a subgraph of the original graph. Formally, given a union of two weighted graphs $G$ and $W$ and an integer $k$, we are asked to find a $k$-edge…

Discrete Mathematics · Computer Science 2009-12-10 Alexandra Kolla , Yury Makarychev , Amin Saberi , Shanghua Teng

Knapsack is one of the most fundamental problems in theoretical computer science. In the $(1 - \epsilon)$-approximation setting, although there is a fine-grained lower bound of $(n + 1 / \epsilon) ^ {2 - o(1)}$ based on the $(\min,…

Data Structures and Algorithms · Computer Science 2025-08-12 Xiao Mao

We present an extremely simple polynomial-space exponential-time $(1-\varepsilon)$-approximation algorithm for MAX-k-SAT that is (slightly) faster than the previous known polynomial-space $(1-\varepsilon)$-approximation algorithms by Hirsch…

Data Structures and Algorithms · Computer Science 2026-04-22 Harry Buhrman , Sevag Gharibian , Zeph Landau , François Le Gall , Norbert Schuch , Suguru Tamaki

We study the family of intersection graphs of low density objects in low dimensional Euclidean space. This family is quite general, and includes planar graphs. We prove that such graphs have small separators. Next, we present efficient…

Computational Geometry · Computer Science 2016-06-01 Sariel Har-Peled , Kent Quanrud

We consider the SUBSET SUM problem and its important variants in this paper. In the SUBSET SUM problem, a (multi-)set $X$ of $n$ positive numbers and a target number $t$ are given, and the task is to find a subset of $X$ with the maximal…

Data Structures and Algorithms · Computer Science 2022-12-07 Xiaoyu Wu , Lin Chen

The minimum-cost $k$-edge-connected spanning subgraph ($k$-ECSS) problem is a generalization and strengthening of the well-studied minimum-cost spanning tree (MST) problem. While the round complexity of distributedly computing the latter…

Data Structures and Algorithms · Computer Science 2022-11-10 Michal Dory , Mohsen Ghaffari

We consider structural parameterizations of the fundamental Dominating Set problem and its variants in the parameter ecology program. We give improved FPT algorithms and lower bounds under well-known conjectures for dominating set in graphs…

Data Structures and Algorithms · Computer Science 2024-05-20 Dishant Goyal , Ashwin Jacob , Kaushtubh Kumar , Diptapriyo Majumdar , Venkatesh Raman

In the \textsc{Maximum Degree Contraction} problem, input is a graph $G$ on $n$ vertices, and integers $k, d$, and the objective is to check whether $G$ can be transformed into a graph of maximum degree at most $d$, using at most $k$ edge…

Data Structures and Algorithms · Computer Science 2020-09-25 Saket Saurabh , Prafullkumar Tale

We develop faster approximation algorithms for Metric-TSP building on recent, nearly linear time approximation schemes for the LP relaxation [Chekuri and Quanrud, 2017]. We show that the LP solution can be sparsified via cut-sparsification…

Data Structures and Algorithms · Computer Science 2018-02-06 Chandra Chekuri , Kent Quanrud

We study the optimization version of constraint satisfaction problems (Max-CSPs) in the framework of parameterized complexity; the goal is to compute the maximum fraction of constraints that can be satisfied simultaneously. In standard…

Computational Complexity · Computer Science 2018-04-24 Holger Dell , Eun Jung Kim , Michael Lampis , Valia Mitsou , Tobias Mömke

We study how well one can recover sparse principal components of a data matrix using a sketch formed from a few of its elements. We show that for a wide class of optimization problems, if the sketch is close (in the spectral norm) to the…

Machine Learning · Computer Science 2015-03-16 Abhisek Kundu , Petros Drineas , Malik Magdon-Ismail

In this paper, we propose a general framework to design {efficient} polynomial time approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization problems. Given an error parameter $\epsilon>0$, such algorithmic…

Data Structures and Algorithms · Computer Science 2025-05-30 Danny Segev , Sahil Singla

We consider the problem of estimating the spectral density of the normalized adjacency matrix of an $n$-node undirected graph. We provide a randomized algorithm that, with $O(n\epsilon^{-2})$ queries to a degree and neighbor oracle and in…

Data Structures and Algorithms · Computer Science 2024-06-12 Yujia Jin , Ishani Karmarkar , Christopher Musco , Aaron Sidford , Apoorv Vikram Singh

We show that for constraint satisfaction problems (CSPs), sub-exponential size linear programming relaxations are as powerful as $n^{\Omega(1)}$-rounds of the Sherali-Adams linear programming hierarchy. As a corollary, we obtain…

Computational Complexity · Computer Science 2018-01-03 Pravesh K. Kothari , Raghu Meka , Prasad Raghavendra

We give an approximation algorithm for non-uniform sparsest cut with the following guarantee: For any $\epsilon,\delta \in (0,1)$, given cost and demand graphs with edge weights $C, D$ respectively, we can find a set $T\subseteq V$ with…

Data Structures and Algorithms · Computer Science 2015-03-19 Venkatesan Guruswami , Ali Kemal Sinop