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In Polyamorous Scheduling, we are given an edge-weighted graph and must find a periodic schedule of matchings in this graph which minimizes the maximal weighted waiting time between consecutive occurrences of the same edge. This NP-hard…

Data Structures and Algorithms · Computer Science 2024-11-12 Yuriy Biktairov , Leszek Gąsieniec , Wanchote Po Jiamjitrak , Namrata , Benjamin Smith , Sebastian Wild

The maximum common subtree isomorphism problem asks for the largest possible isomorphism between subtrees of two given input trees. This problem is a natural restriction of the maximum common subgraph problem, which is ${\sf NP}$-hard in…

Data Structures and Algorithms · Computer Science 2016-08-23 Andre Droschinsky , Nils M. Kriege , Petra Mutzel

We investigate the complexity of several fundamental polynomial-time solvable problems on graphs and on matrices, when the given instance has low treewidth; in the case of matrices, we consider the treewidth of the graph formed by non-zero…

Data Structures and Algorithms · Computer Science 2015-11-05 Fedor V. Fomin , Daniel Lokshtanov , Michał Pilipczuk , Saket Saurabh , Marcin Wrochna

We give a quasipolynomial-time algorithm for learning stochastic decision trees that is optimally resilient to adversarial noise. Given an $\eta$-corrupted set of uniform random samples labeled by a size-$s$ stochastic decision tree, our…

Machine Learning · Computer Science 2021-05-11 Guy Blanc , Jane Lange , Li-Yang Tan

We study the complexity of approximate representation and learning of submodular functions over the uniform distribution on the Boolean hypercube $\{0,1\}^n$. Our main result is the following structural theorem: any submodular function is…

Machine Learning · Computer Science 2013-04-03 Vitaly Feldman , Pravesh Kothari , Jan Vondrak

We study computational and statistical aspects of learning Latent Markov Decision Processes (LMDPs). In this model, the learner interacts with an MDP drawn at the beginning of each epoch from an unknown mixture of MDPs. To sidestep known…

Machine Learning · Computer Science 2024-06-13 Fan Chen , Constantinos Daskalakis , Noah Golowich , Alexander Rakhlin

There are many classical problems in P whose time complexities have not been improved over the past decades. Recent studies of "Hardness in P" have revealed that, for several of such problems, the current fastest algorithm is the best…

Data Structures and Algorithms · Computer Science 2017-10-24 Yoichi Iwata , Tomoaki Ogasawara , Naoto Ohsaka

We give a deterministic polynomial time $2^{O(r)}$-approximation algorithm for the number of bases of a given matroid of rank $r$ and the number of common bases of any two matroids of rank $r$. To the best of our knowledge, this is the…

Data Structures and Algorithms · Computer Science 2018-11-06 Nima Anari , Shayan Oveis Gharan , Cynthia Vinzant

We prove the following result about approximating the maximum independent set in a graph. Informally, we show that any approximation algorithm with a ``non-trivial'' approximation ratio (as a function of the number of vertices of the input…

Data Structures and Algorithms · Computer Science 2023-07-06 Parinya Chalermsook , Fedor Fomin , Thekla Hamm , Tuukka Korhonen , Jesper Nederlof , Ly Orgo

In the $d$-Scattered Set problem we are asked to select at least $k$ vertices of a given graph, so that the distance between any pair is at least $d$. We study the problem's (in-)approximability and offer improvements and extensions of…

Computational Complexity · Computer Science 2019-10-15 Ioannis Katsikarelis , Michael Lampis , Vangelis Th. Paschos

We give a deterministic algorithm for approximately counting satisfying assignments of a degree-$d$ polynomial threshold function (PTF). Given a degree-$d$ input polynomial $p(x_1,\dots,x_n)$ over $R^n$ and a parameter $\epsilon> 0$, our…

Computational Complexity · Computer Science 2013-12-02 Anindya De , Rocco Servedio

Given an $\mathbb{N}$-weighted tree automaton, we give a decision procedure for exponential vs polynomial growth (with respect to the input size) in quadratic time, and an algorithm that computes the exact polynomial degree of growth in…

Formal Languages and Automata Theory · Computer Science 2026-01-07 Paul Gallot , Nathan Lhote , Lê Thành Dũng Nguyên

The $\epsilon$-approximate degree of a Boolean function $f: \{-1, 1\}^n \to \{-1, 1\}$ is the minimum degree of a real polynomial that approximates $f$ to within $\epsilon$ in the $\ell_\infty$ norm. We prove several lower bounds on this…

Computational Complexity · Computer Science 2014-03-25 Mark Bun , Justin Thaler

We initiate a systematic study of utilizing predictions to improve over approximation guarantees of classic algorithms, without increasing the running time. We propose a systematic method for a wide class of optimization problems that ask…

Data Structures and Algorithms · Computer Science 2024-11-26 Antonios Antoniadis , Marek Eliáš , Adam Polak , Moritz Venzin

We study the problem of partitioning a set of $n$ objects in a metric space into $k$ clusters $V_1,\dots,V_k$. The quality of the clustering is measured by considering the vector of cluster costs and then minimizing some monotone symmetric…

Data Structures and Algorithms · Computer Science 2025-01-10 Matthias Kaul , Kelin Luo , Matthias Mnich , Heiko Röglin

Given a finite metric space $(X\cup Y, \mathbf{d})$ the $k$-median problem is to find a set of $k$ centers $C\subseteq Y$ that minimizes $\sum_{p\in X} \min_{c\in C} \mathbf{d}(p,c)$. In general metrics, the best polynomial time algorithm…

Data Structures and Algorithms · Computer Science 2026-03-26 Anne Driemel , Jan Höckendorff , Ioannis Psarros , Christian Sohler , Di Yue

Celebrated work of Jerrum, Sinclair, and Vigoda has established that the permanent of a {0,1} matrix can be approximated in randomized polynomial time by using a rapidly mixing Markov chain. A separate strand of the literature has pursued…

Computational Complexity · Computer Science 2009-06-10 Cristopher Moore , Alexander Russell

In this short paper, we present an improved algorithm for approximating the minimum cut on distributed (CONGEST) networks. Let $\lambda$ be the minimum cut. Our algorithm can compute $\lambda$ exactly in…

Data Structures and Algorithms · Computer Science 2014-05-16 Danupon Nanongkai

Tensor network contractions are widely used in statistical physics, quantum computing, and computer science. We introduce a method to efficiently approximate tensor network contractions using low-rank approximations, where each intermediate…

Quantum Physics · Physics 2025-01-01 Linjian Ma , Matthew Fishman , Miles Stoudenmire , Edgar Solomonik

This paper is devoted to the explicit construction of optimal designs for discrimination between two polynomial regression models of degree $n-2$ and $n$. In a fundamental paper, Atkinson and Fedorov [Biometrika 62 (1975a) 57--70] proposed…

Statistics Theory · Mathematics 2012-05-30 Holger Dette , Viatcheslav B. Melas , Petr Shpilev