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What is the minimum amount of information and time needed to solve 2SAT? When the instance is known, it can be solved in polynomial time, but is this also possible without knowing the instance? Bei, Chen and Zhang (STOC '13) considered a…

Computational Complexity · Computer Science 2016-06-14 Itai Arad , Adam Bouland , Daniel Grier , Miklos Santha , Aarthi Sundaram , Shengyu Zhang

Multi-homogeneous polynomial systems arise in many applications. We provide bit complexity estimates for solving them which, up to a few extra other factors, are quadratic in the number of solutions and linear in the height of the input…

Symbolic Computation · Computer Science 2017-12-12 Mohab Safey El Din , Eric Schost

We initiate a study of locally decodable codes with randomized encoding. Standard locally decodable codes are error correcting codes with a deterministic encoding function and a randomized decoding function, such that any desired message…

Information Theory · Computer Science 2020-01-14 Kuan Cheng , Xin Li , Yu Zheng

We introduce the problem of learning mixtures of $k$ subcubes over $\{0,1\}^n$, which contains many classic learning theory problems as a special case (and is itself a special case of others). We give a surprising $n^{O(\log k)}$-time…

Machine Learning · Computer Science 2019-02-20 Sitan Chen , Ankur Moitra

One of the fundamental open problems in the area of distributed graph algorithms is the question of whether randomization is needed for efficient symmetry breaking. While there are fast, $\text{poly}\log n$-time randomized distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-29 Philipp Bamberger , Mohsen Ghaffari , Fabian Kuhn , Yannic Maus , Jara Uitto

In a distinguishing problem, the input is a sample drawn from one of two distributions and the algorithm is tasked with identifying the source distribution. The performance of a distinguishing algorithm is measured by its advantage, i.e.,…

Computational Complexity · Computer Science 2025-07-22 Ansh Nagda , Prasad Raghavendra

In the noisy population recovery problem of Dvir et al., the goal is to learn an unknown distribution $f$ on binary strings of length $n$ from noisy samples. For some parameter $\mu \in [0,1]$, a noisy sample is generated by flipping each…

Computational Complexity · Computer Science 2016-02-25 Anindya De , Michael Saks , Sijian Tang

We consider the problem of clustering in the learning-augmented setting, where we are given a data set in $d$-dimensional Euclidean space, and a label for each data point given by an oracle indicating what subsets of points should be…

Machine Learning · Computer Science 2023-03-02 Thy Nguyen , Anamay Chaturvedi , Huy Lê Nguyen

In this paper we consider a scenario where there are several algorithms for solving a given problem. Each algorithm is associated with a probability of success and a cost, and there is also a penalty for failing to solve the problem. The…

Data Structures and Algorithms · Computer Science 2020-08-11 Shlomo Moran , Irad Yavneh

Phase estimation, due to Kitaev [arXiv'95], is one of the most fundamental subroutines in quantum computing. In the basic scenario, one is given black-box access to a unitary $U$, and an eigenstate $\lvert \psi \rangle$ of $U$ with unknown…

Quantum Physics · Physics 2025-12-15 Nikhil S. Mande , Ronald de Wolf

Despite the relevance of the binomial distribution for probability theory and applied statistical inference, its higher-order moments are poorly understood. The existing formulas are either not general enough, or not structured and…

Statistics Theory · Mathematics 2022-06-07 Maciej Skorski

It is folklore particularly in numerical and computer sciences that, instead of solving some general problem f:A->B, additional structural information about the input x in A (that is any kind of promise that x belongs to a certain subset A'…

Computational Complexity · Computer Science 2009-09-02 Martin Ziegler

In $masked\ low-rank\ approximation$, one is given $A \in \mathbb{R}^{n \times n}$ and binary mask matrix $W \in \{0,1\}^{n \times n}$. The goal is to find a rank-$k$ matrix $L$ for which: $$cost(L) = \sum_{i=1}^{n} \sum_{j = 1}^{n} W_{i,j}…

Data Structures and Algorithms · Computer Science 2020-12-01 Cameron Musco , Christopher Musco , David P. Woodruff

Using elementary rigorous methods we prove the existence of a clustered phase in the random $K$-SAT problem, for $K\geq 8$. In this phase the solutions are grouped into clusters which are far away from each other. The results are in…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Mezard , T. Mora , R. Zecchina

Is detecting a $k$-clique in $k$-partite regular (hyper-)graphs as hard as in the general case? Intuition suggests yes, but proving this -- especially for hypergraphs -- poses notable challenges. Concretely, we consider a strong notion of…

Computational Complexity · Computer Science 2026-05-12 Nick Fischer , Marvin Künnemann , Mirza Redžić , Julian Stieß

In this paper, we consider the weighted online set k-multicover problem. In this problem, we have a universe V of elements, a family S of subsets of V with a positive real cost for every set in S and a "coverage factor" (positive integer)…

Data Structures and Algorithms · Computer Science 2015-03-19 Piotr Berman , Bhaskar DasGupta

We study the parameterized complexity of algorithmic problems whose input is an integer set $A$ in terms of the doubling constant $C := |A + A|/|A|$, a fundamental measure of additive structure. We present evidence that this new…

Data Structures and Algorithms · Computer Science 2024-07-26 Tim Randolph , Karol Węgrzycki

We analyze the competitive ratio and the advice complexity of the online unbounded knapsack problem. An instance is given as a sequence of n items with a size and a value each, and an algorithm has to decide how often to pack each item into…

Data Structures and Algorithms · Computer Science 2024-11-01 Hans-Joachim Böckenhauer , Matthias Gehnen , Juraj Hromkovič , Ralf Klasing , Dennis Komm , Henri Lotze , Daniel Mock , Peter Rossmanith , Moritz Stocker

Shared randomness is a valuable resource in distributed computing, allowing some form of coordination between processors without explicit communication. But what happens when the shared random string can affect the inputs to the system?…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-05 Adar Hadad , Moni Naor

In this paper, we study the quantity of computational resources (state machine states and/or probabilistic transition precision) needed to solve specific problems in a single hop network where nodes communicate using only beeps. We begin by…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-18 Seth Gilbert , Calvin Newport
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