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We consider the O(n) loop model on tetravalent maps and show how to rephrase it into a model of bipartite maps without loops. This follows from a combinatorial decomposition that consists in cutting the O(n) model configurations along their…

Mathematical Physics · Physics 2011-12-30 G. Borot , J. Bouttier , E. Guitter

We consider the problems of maintaining an approximate maximum matching and an approximate minimum vertex cover in a dynamic graph undergoing a sequence of edge insertions/deletions. Starting with the seminal work of Onak and Rubinfeld…

Data Structures and Algorithms · Computer Science 2016-11-21 Sayan Bhattacharya , Deeparnab Chakrabarty , Monika Henzinger

We present a deterministic dynamic algorithm for maintaining a $(1+\epsilon)f$-approximate minimum cost set cover with $O(f\log(Cn)/\epsilon^2)$ amortized update time, when the input set system is undergoing element insertions and…

Data Structures and Algorithms · Computer Science 2019-09-26 Sayan Bhattacharya , Monika Henzinger , Danupon Nanongkai

In the online sorting problem, a sequence of $n$ numbers in $[0, 1]$ (including $\{0,1\}$) have to be inserted in an array of size $m \ge n$ so as to minimize the sum of absolute differences between pairs of numbers occupying consecutive…

Data Structures and Algorithms · Computer Science 2025-08-21 Yossi Azar , Debmalya Panigrahi , Or Vardi

We consider the problem of estimating the factors of a rank-$1$ matrix with i.i.d. Gaussian, rank-$1$ measurements that are nonlinearly transformed and corrupted by noise. Considering two prototypical choices for the nonlinearity, we study…

Optimization and Control · Mathematics 2024-10-02 Kabir Aladin Chandrasekher , Mengqi Lou , Ashwin Pananjady

We present an algorithm for marginalising changepoints in time-series models that assume a fixed number of unknown changepoints. Our algorithm is differentiable with respect to its inputs, which are the values of latent random variables…

Machine Learning · Computer Science 2019-11-25 Hyoungjin Lim , Gwonsoo Che , Wonyeol Lee , Hongseok Yang

This paper studies the online scheduling problem of minimizing total flow time for $n$ jobs on $m$ identical machines. A classical $\Omega(n)$ lower bound shows that no deterministic single-machine algorithm can beat the trivial greedy,…

Data Structures and Algorithms · Computer Science 2026-04-02 Yutong Geng , Enze Sun , Zonghan Yang , Yuhao Zhang

Randomized sampling has recently been demonstrated to be an efficient technique for computing approximate low-rank factorizations of matrices for which fast methods for computing matrix vector products are available. This paper describes an…

Numerical Analysis · Mathematics 2008-06-17 Per-Gunnar Martinsson

Given n elements with nonnegative integer weights w1,..., wn and an integer capacity C, we consider the counting version of the classic knapsack problem: find the number of distinct subsets whose weights add up to at most the given…

Data Structures and Algorithms · Computer Science 2010-08-11 Daniel Stefankovic , Santosh Vempala , Eric Vigoda

We consider the Partition problem and propose a deterministic FPTAS (Fully Polynomial-Time Approximation Scheme) that runs in $\widetilde{O}(n + 1/\varepsilon)$-time. This is the best possible (up to a polylogarithmic factor) assuming the…

Data Structures and Algorithms · Computer Science 2025-01-23 Lin Chen , Jiayi Lian , Yuchen Mao , Guochuan Zhang

In this letter, we study the deterministic sampling patterns for the completion of low rank matrix, when corrupted with a sparse noise, also known as robust matrix completion. We extend the recent results on the deterministic sampling…

Information Theory · Computer Science 2018-03-14 Morteza Ashraphijuo , Vaneet Aggarwal , Xiaodong Wang

In this paper we consider word equations with one variable (and arbitrary many appearances of it). A recent technique of recompression, which is applicable to general word equations, is shown to be suitable also in this case. While in…

Formal Languages and Automata Theory · Computer Science 2014-01-23 Artur Jeż

We study a family of sorting match puzzles on grids, which we call permutation match puzzles. In this puzzle, each row and column of a $n \times n$ grid is labeled with an ordering constraint -- ascending (A) or descending (D) -- and the…

Data Structures and Algorithms · Computer Science 2026-03-12 Kshitij Gajjar , Neeldhara Misra

In a group testing scheme, a set of tests is designed to identify a small number $t$ of defective items that are present among a large number $N$ of items. Each test takes as input a group of items and produces a binary output indicating…

Information Theory · Computer Science 2016-11-17 Arya Mazumdar

In content-oblivious computation, n nodes wish to compute a given task over an asynchronous network that suffers from an extremely harsh type of noise, which corrupts the content of all messages across all channels. In a recent work,…

Data Structures and Algorithms · Computer Science 2024-05-07 Fabian Frei , Ran Gelles , Ahmed Ghazy , Alexandre Nolin

The random access problem for compressed strings is to build a data structure that efficiently supports accessing the character in position $i$ of a string given in compressed form. Given a grammar of size $n$ compressing a string of size…

Data Structures and Algorithms · Computer Science 2015-01-27 Patrick Hagge Cording

Given a text $T$ of length $n$, we propose a deterministic online algorithm computing the sparse suffix array and the sparse longest common prefix array of $T$ in $O(c \sqrt{\lg n} + m \lg m \lg n \lg^* n)$ time with $O(m)$ words of space…

Data Structures and Algorithms · Computer Science 2018-03-26 Johannes Fischer , Tomohiro I , Dominik Köppl

We consider Oblivious Shuffling and K-Oblivious Shuffling, a refinement thereof. We provide efficient algorithms for both and discuss their application to the design of Oblivious RAM. The task of K-Oblivious Shuffling is to obliviously…

Cryptography and Security · Computer Science 2017-10-19 Sarvar Patel , Giuseppe Persiano , Kevin Yeo

We develop a technique to design efficiently computable estimators for sparse linear regression in the simultaneous presence of two adversaries: oblivious and adaptive. We design several robust algorithms that outperform the state of the…

Machine Learning · Computer Science 2024-11-01 Chih-Hung Liu , Gleb Novikov

We consider the problem of sorting $n$ elements subject to persistent random comparison errors. In this problem, each comparison between two elements can be wrong with some fixed (small) probability $p$, and comparing the same pair of…

Data Structures and Algorithms · Computer Science 2025-08-28 Barbara Geissmann , Stefano Leucci , Chih-Hung Liu , Paolo Penna