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Related papers: Average-Case Subset Balancing Problems

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Noisy $k$-XOR is a basic average-case inference problem in which one observes random noisy $k$-ary parity constraints and seeks to recover, or more weakly, detect, a hidden Boolean assignment. A central question is to characterize the…

Computational Complexity · Computer Science 2026-04-14 Songtao Mao

The (Non-Preemptive) Throughput Maximization problem is a natural and fundamental scheduling problem. We are given $n$ jobs, where each job $j$ is characterized by a processing time and a time window, contained in a global interval $[0,T)$,…

Data Structures and Algorithms · Computer Science 2026-04-01 Alexander Armbruster , Fabrizio Grandoni , Antoine Tinguely , Andreas Wiese

Given a constraint satisfaction problem (CSP) on $n$ variables, $x_1, x_2, \dots, x_n \in \{\pm 1\}$, and $m$ constraints, a global cardinality constraint has the form of $\sum_{i = 1}^{n} x_i = (1-2p)n$, where $p \in (\Omega(1), 1 -…

Data Structures and Algorithms · Computer Science 2016-10-21 Xue Chen , Yuan Zhou

The main purpose of this paper is to study the NP-complete subset-sum problem, not in the usual context of time-complexity-based classification of the algorithms (exponential/polynomial), but through a new kind of algorithmic classification…

Computational Complexity · Computer Science 2018-11-20 Antonios Syreloglou

In seeking out an algorithm to test out the capability of the IBM Quantum Experience quantum computer, we were given a review paper covering various algorithms for solving the subset-sum problem, including both classical and quantum…

Emerging Technologies · Computer Science 2019-12-09 David Gunter , Toks Adedoyin

Clustering is a fundamental problem in unsupervised machine learning with many applications in data analysis. Popular clustering algorithms such as Lloyd's algorithm and $k$-means++ can take $\Omega(ndk)$ time when clustering $n$ points in…

Machine Learning · Computer Science 2023-10-26 Moses Charikar , Monika Henzinger , Lunjia Hu , Maxmilian Vötsch , Erik Waingarten

We study the problem of high-dimensional sparse mean estimation in the presence of an $\epsilon$-fraction of adversarial outliers. Prior work obtained sample and computationally efficient algorithms for this task for identity-covariance…

Data Structures and Algorithms · Computer Science 2024-07-08 Ilias Diakonikolas , Daniel M. Kane , Sushrut Karmalkar , Ankit Pensia , Thanasis Pittas

We resolve a long-standing open question, about the existence of a constant-factor approximation algorithm for the average-case \textsc{Decision Tree} problem with uniform probability distribution over the hypotheses. We answer the question…

Data Structures and Algorithms · Computer Science 2026-04-29 Michał Szyfelbein

The interval subset sum problem (ISSP) is a generalization of the well-known subset sum problem. Given a set of intervals $\left\{[a_{i,1},a_{i,2}]\right\}_{i=1}^n$ and a target integer $T,$ the ISSP is to find a set of integers, at most…

Data Structures and Algorithms · Computer Science 2017-04-25 Rui Diao , Ya-Feng Liu , Yu-Hong Dai

We study the Euclidean minimum weight perfect matching problem for $n$ points in the plane. It is known that any deterministic approximation algorithm whose approximation ratio depends only on $n$ requires at least $\Omega(n \log n)$ time.…

Computational Geometry · Computer Science 2026-01-09 Stefan Hougardy , Karolina Tammemaa

The index coding problem is concerned with broadcasting encoded information to a collection of receivers in a way that enables each receiver to discover its required data based on its side information, which comprises the data required by…

Data Structures and Algorithms · Computer Science 2024-08-19 Dror Chawin , Ishay Haviv

We consider an $n$ agents distributed optimization problem with imperfect information characterized in a parametric sense, where the unknown parameter can be solved by a distinct distributed parameter learning problem. Though each agent…

Optimization and Control · Mathematics 2024-04-23 Yaqun Yang , Jinlong Lei

The Subset-Sums Ratio problem (SSR) is an optimization problem in which, given a set of integers, the goal is to find two subsets such that the ratio of their sums is as close to 1 as possible. In this paper we develop a new FPTAS for the…

Data Structures and Algorithms · Computer Science 2019-12-20 Nikolaos Melissinos , Aris Pagourtzis

This paper is concerned with the $1||\sum p_jU_j$ problem, the problem of minimizing the total processing time of tardy jobs on a single machine. This is not only a fundamental scheduling problem, but also a very important problem from a…

Data Structures and Algorithms · Computer Science 2020-04-22 Karl Bringmann , Nick Fischer , Danny Hermelin , Dvir Shabtay , Philip Wellnitz

Apart from the principles and methodologies inherited from Economics and Game Theory, the studies in Algorithmic Mechanism Design typically employ the worst-case analysis and approximation schemes of Theoretical Computer Science. For…

Computer Science and Game Theory · Computer Science 2017-12-15 Jie Zhang

We develop a randomized approximation algorithm for the classical maximum coverage problem, which given a list of sets $A_1,A_2,\cdots, A_m$ and integer parameter $k$, select $k$ sets $A_{i_1}, A_{i_2},\cdots, A_{i_k}$ for maximum union…

Data Structures and Algorithms · Computer Science 2016-07-21 Bin Fu

The Subset Sum Problem is a fundamental NP-complete problem in cryptography and combinatorial optimization, with many real-world applications. The Random Subset Sum Problem (RSSP) is a more applicable version of subset sum, where numbers…

Data Structures and Algorithms · Computer Science 2026-05-21 Edwin Chen , Christof Teuscher

We describe a practical algorithm for computing normal forms for semigroups and monoids with finite presentations satisfying so-called small overlap conditions. Small overlap conditions are natural conditions on the relations in a…

Formal Languages and Automata Theory · Computer Science 2023-05-05 James D. Mitchell , Maria Tsalakou

This paper investigates the optimal ergodic sublinear convergence rate of the relaxed proximal point algorithm for solving monotone variational inequality problems. The exact worst case convergence rate is computed using the performance…

Optimization and Control · Mathematics 2019-07-15 Guoyong Gu , Junfeng Yang

We present algorithms for length-constrained maximum sum segment and maximum density segment problems, in particular, and the problem of finding length-constrained heaviest segments, in general, for a sequence of real numbers. Given a…

Computational Geometry · Computer Science 2015-03-19 Md. Shafiul Alam , Asish Mukhopadhyay