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We give new rounding schemes for SDP relaxations for the problems of maximizing cubic polynomials over the unit sphere and the $n$-dimensional hypercube. In both cases, the resulting algorithms yield a $O(\sqrt{n/k})$ multiplicative…

Data Structures and Algorithms · Computer Science 2023-10-03 Jun-Ting Hsieh , Pravesh K. Kothari , Lucas Pesenti , Luca Trevisan

Sumsets are central objects in additive combinatorics. In 2007, Granville asked whether one can efficiently recognize whether a given set $S$ is a sumset, i.e. whether there is a set $A$ such that $A+A=S$. Granville suggested an algorithm…

Data Structures and Algorithms · Computer Science 2024-10-29 Amir Abboud , Nick Fischer , Ron Safier , Nathan Wallheimer

Allocation of samples in stratified and/or multistage sampling is one of the central issues of sampling theory. In a survey of a population often the constraints for precision of estimators of subpopulations parameters have to be taken care…

Statistics Theory · Mathematics 2015-03-31 Jacek Wesolowski , Robert Wieczorkowski

We study the design of polylogarithmic depth algorithms for approximately solving packing and covering semidefinite programs (or positive SDPs for short). This is a natural SDP generalization of the well-studied positive LP problem.…

Data Structures and Algorithms · Computer Science 2016-01-12 Zeyuan Allen-Zhu , Yin Tat Lee , Lorenzo Orecchia

In this work, we consider the Submodular Maximization under Knapsack (SMK) constraint problem over the ground set of size $n$. The problem recently attracted a lot of attention due to its applications in various domains of combination…

Data Structures and Algorithms · Computer Science 2024-05-22 Canh V. Pham

This paper analyzes to what extent it is possible to efficiently reduce the number of clauses in NP-hard satisfiability problems, without changing the answer. Upper and lower bounds are established using the concept of kernelization.…

Computational Complexity · Computer Science 2019-07-01 Bart M. P. Jansen , Astrid Pieterse

We consider estimation models of the form $Y=X^*+N$, where $X^*$ is some $m$-dimensional signal we wish to recover, and $N$ is symmetrically distributed noise that may be unbounded in all but a small $\alpha$ fraction of the entries. We…

Machine Learning · Computer Science 2022-11-15 Tommaso d'Orsi , Rajai Nasser , Gleb Novikov , David Steurer

We study the classical scheduling problem on parallel machines %with precedence constraints where the precedence graph has the bounded depth $h$. Our goal is to minimize the maximum completion time. We focus on developing approximation…

Data Structures and Algorithms · Computer Science 2023-02-02 Bin Fu , Yumei Huo , Hairong Zhao

We describe a deterministic algorithm that computes an approximate root of n complex polynomial equations in n unknowns in average polynomial time with respect to the size of the input, in the Blum-Shub-Smale model with square root. It…

Numerical Analysis · Mathematics 2023-06-12 Pierre Lairez

We give a highly efficient "semi-agnostic" algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let $p$ be an arbitrary distribution over an interval $I$ which is…

Machine Learning · Computer Science 2013-05-15 Siu-On Chan , Ilias Diakonikolas , Rocco A. Servedio , Xiaorui Sun

Motivated by the philosophy and phenomenal success of compressed sensing, the problem of reconstructing a matrix from a sampling of its entries has attracted much attention recently. Such a problem can be viewed as an information-theoretic…

Information Theory · Computer Science 2009-05-15 Zhisu Zhu , Anthony Man-Cho So , Yinyu Ye

Many streaming algorithms provide only a high-probability relative approximation. These two relaxations, of allowing approximation and randomization, seem necessary -- for many streaming problems, both relaxations must be employed…

Data Structures and Algorithms · Computer Science 2023-05-16 Vladimir Braverman , Robert Krauthgamer , Aditya Krishnan , Shay Sapir

Given a fixed arity $k \geq 2$, Min-$k$-CSP on complete instances involves a set of $n$ variables $V$ and one nontrivial constraint for every $k$-subset of variables (so there are $\binom{n}{k}$ constraints). The goal is to find an…

Data Structures and Algorithms · Computer Science 2024-10-28 Aditya Anand , Euiwoong Lee , Amatya Sharma

The Exact Satisfiability problem asks if we can find a satisfying assignment to each clause such that exactly one literal in each clause is assigned $1$, while the rest are all assigned $0$. We can generalise this problem further by…

Data Structures and Algorithms · Computer Science 2021-08-02 Gordon Hoi , Frank Stephan

We present a new algorithm for enumerating bubbles with length constraints in directed graphs. This problem arises in transcriptomics, where the question is to identify all alternative splicing events present in a sample of mRNAs sequenced…

Quantitative Methods · Quantitative Biology 2013-08-02 Gustavo Sacomoto , Vincent Lacroix , Marie-France Sagot

Density level sets can be estimated using plug-in methods, excess mass algorithms or a hybrid of the two previous methodologies. The plug-in algorithms are based on replacing the unknown density by some nonparametric estimator, usually the…

Statistics Theory · Mathematics 2016-11-26 A. Rodríguez-Casal , P. Saavedra-Nieves

One specific subset of quantum algorithms is Grovers Ordered Search Problem (OSP), the quantum counterpart of the classical binary search algorithm, which utilizes oracle functions to produce a specified value within an ordered database.…

Quantum Physics · Physics 2017-01-24 Jupinder Parmar , Saarim Rahman , Jesse Thiara

To partition a sequence of n integers into subsets with prescribed sums is an NP-hard problem in general. In this paper we present an efficient solution for the homogeneous version of this problem; i.e. where the elements in each subset add…

Combinatorics · Mathematics 2018-07-17 Alexander Büchel , Ulrich Gilleßen , Kurt-Ulrich Witt

Let $A$ be a sequence of $n \geq 0$ real numbers. A subsequence of $A$ is a sequence of contiguous elements of $A$. A \emph{maximum scoring subsequence} of $A$ is a subsequence with largest sum of its elements, which can be found in O(n)…

Data Structures and Algorithms · Computer Science 2013-03-21 Ricardo C. Corrêa , Pablo M. S. Farias , Críston P. de Souza

Integer linear programs $\min\{c^T x : A x = b, x \in \mathbb{Z}^n_{\ge 0}\}$, where $A \in \mathbb{Z}^{m \times n}$, $b \in \mathbb{Z}^m$, and $c \in \mathbb{Z}^n$, can be solved in pseudopolynomial time for any fixed number of constraints…

Data Structures and Algorithms · Computer Science 2024-09-06 Lars Rohwedder , Karol Węgrzycki