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The bin packing problem is to find the minimum number of bins of size one to pack a list of items with sizes $a_1,..., a_n$ in $(0,1]$. Using uniform sampling, which selects a random element from the input list each time, we develop a…

Computational Complexity · Computer Science 2011-02-25 Richard Beigel , Bin Fu

Consider the classical Min-Sum Set Cover problem: We are given a universe $\mathcal{U}$ of $n$ elements and a collection $\mathcal{S}$ of $k$ subsets of $\mathcal{U}$. Moreover, a cost function is associated with each set. The goal is to…

Data Structures and Algorithms · Computer Science 2026-05-29 Michał Szyfelbein

Constrained submodular maximization problems encompass a wide variety of applications, including personalized recommendation, team formation, and revenue maximization via viral marketing. The massive instances occurring in modern day…

Data Structures and Algorithms · Computer Science 2024-02-20 Georgios Amanatidis , Federico Fusco , Philip Lazos , Stefano Leonardi , Rebecca Reiffenhäuser

In this paper, we revisit the much studied problem of Pattern Matching with Swaps (Swap Matching problem, for short). We first present a graph-theoretic model, which opens a new and so far unexplored avenue to solve the problem. Then, using…

Data Structures and Algorithms · Computer Science 2013-09-19 Pritom Ahmed , Costas S. Iliopoulos , A. S. M. Sohidull Islam , M. Sohel Rahman

Consider $n$ independent, biased coins, each with a known probability of heads. Presented with an ordering of these coins, flip (i.e., toss) each coin once, in that order, until we have observed both a *head* and a *tail*, or flipped all…

Data Structures and Algorithms · Computer Science 2025-10-21 Feyza Duman Keles , Lisa Hellerstein , Kunal Marwaha , Christopher Musco , Xinchen Yang

Given a set of coins arranged in a line, we remove heads-up coins one at a time and flip any adjacent coins after each removal. The coin-removal problem is to determine for which arrangements of coins it is possible to remove all of the…

Combinatorics · Mathematics 2007-05-23 Kennan Shelton , Michael Siler

We present a pseudopolynomial-time algorithm for the Knapsack problem that has running time $\widetilde{O}(n + t\sqrt{p_{\max}})$, where $n$ is the number of items, $t$ is the knapsack capacity, and $p_{\max}$ is the maximum item profit.…

Data Structures and Algorithms · Computer Science 2024-07-02 Karl Bringmann , Anita Dürr , Adam Polak

Symmetric submodular maximization is an important class of combinatorial optimization problems, including MAX-CUT on graphs and hyper-graphs. The state-of-the-art algorithm for the problem over general constraints has an approximation ratio…

Data Structures and Algorithms · Computer Science 2024-06-21 Zongqi Wan , Jialin Zhang , Xiaoming Sun , Zhijie Zhang

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

Subset sum is a very old and fundamental problem in theoretical computer science. In this problem, $n$ items with weights $w_1, w_2, w_3, \ldots, w_n$ are given as input and the goal is to find out if there is a subset of them whose weights…

Data Structures and Algorithms · Computer Science 2022-09-13 Hamed Saleh , Saeed Seddighin

We address a well-known problem in combinatorics involving the identification of counterfeit coins with a systematic approach. The methodology can be applied to cases where the total number of coins is exceedingly large such that brute…

Combinatorics · Mathematics 2009-05-04 Eldin Wee Chuan Lim

We consider the problem of sorting $n$ items, given the outcomes of $m$ pre-existing comparisons. We present a simple and natural deterministic algorithm that runs in $O(m + \log T)$ time and does $O(\log T)$ comparisons, where $T$ is the…

Data Structures and Algorithms · Computer Science 2026-05-06 Bernhard Haeupler , Richard Hladík , John Iacono , Vaclav Rozhon , Robert Tarjan , Jakub Tětek

Sequence partition problems arise in many fields, such as sequential data analysis, information transmission, and parallel computing. In this paper, we study the following partition problem variant: given a sequence of $n$ items…

Data Structures and Algorithms · Computer Science 2022-10-12 Kai Jin , Danna Zhang , Canhui Zhang

In the past decade, many parameterized algorithms were developed for packing problems. Our goal is to obtain tradeoffs that improve the running times of these algorithms at the cost of computing approximate solutions. Consider a packing…

Data Structures and Algorithms · Computer Science 2015-05-05 Meirav Zehavi

In the classical Subset Sum problem we are given a set $X$ and a target $t$, and the task is to decide whether there exists a subset of $X$ which sums to $t$. A recent line of research has resulted in $\tilde{O}(t)$-time algorithms, which…

Data Structures and Algorithms · Computer Science 2023-04-25 Karl Bringmann , Vasileios Nakos

We consider the classical makespan minimization scheduling problem where $n$ jobs must be scheduled on $m$ identical machines. Using weighted random sampling, we developed two sublinear time approximation schemes: one for the case where $n$…

Data Structures and Algorithms · Computer Science 2026-05-05 Bin Fu , Yumei Huo , Hairong Zhao

We consider the problem of minimizing the total processing time of tardy jobs on a single machine. This is a classical scheduling problem, first considered by [Lawler and Moore 1969], that also generalizes the Subset Sum problem. Recently,…

Data Structures and Algorithms · Computer Science 2023-01-18 Baruch Schieber , Pranav Sitaraman

We consider the canonical Subset Sum problem: given a list of positive integers $a_1,\ldots,a_n$ and a target integer $t$ with $t > a_i$ for all $i$, determine if there is an $S \subseteq [n]$ such that $\sum_{i \in S} a_i = t$. The…

Data Structures and Algorithms · Computer Science 2020-11-10 Ce Jin , Nikhil Vyas , Ryan Williams

In the classical quickest change detection problem, an observer performs a single experiment to monitor a stochastic process. The goal in the classical problem is to detect a change in the statistical properties of the process, with the…

Signal Processing · Electrical Eng. & Systems 2025-10-08 Patrick Vincent N. Lubenia , Taposh Banerjee

We study the problem of learning a most biased coin among a set of coins by tossing the coins adaptively. The goal is to minimize the number of tosses until we identify a coin i* whose posterior probability of being most biased is at least…

Data Structures and Algorithms · Computer Science 2013-09-10 Karthekeyan Chandrasekaran , Richard Karp