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Related papers: Impatient PPSZ -- a Faster algorithm for CSP

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PPSZ, for long time the fastest known algorithm for $k$-SAT, works by going through the variables of the input formula in random order; each variable is then set randomly to $0$ or $1$, unless the correct value can be inferred by an…

Data Structures and Algorithms · Computer Science 2024-08-07 Dominik Scheder

The PPSZ algorithm by Paturi, Pudl\'ak, Saks, and Zane (FOCS 1998) is the fastest known algorithm for (Promise) Unique k-SAT. We give an improved algorithm with exponentially faster bounds for Unique 3-SAT. For uniquely satisfiable 3-CNF…

Computational Complexity · Computer Science 2014-02-18 Timon Hertli

We analyze the so-called ppz algorithm for (d,k)-CSP problems for general values of d (number of values a variable can take) and k (number of literals per constraint). To analyze its success probability, we prove a correlation inequality…

Data Structures and Algorithms · Computer Science 2010-10-28 Dominik Scheder

Constraint satisfaction problems (CSPs) models many important intractable NP-hard problems such as propositional satisfiability problem (SAT). Algorithms with non-trivial upper bounds on running time for restricted SAT with bounded clause…

Data Structures and Algorithms · Computer Science 2008-01-22 Liang Li , Xin Li , Tian Liu , Ke Xu

We construct uniquely satisfiable $k$-CNF formulas that are hard for the algorithm PPSZ. Firstly, we construct graph-instances on which "weak PPSZ" has savings of at most $(2 + \epsilon) / k$; the saving of an algorithm on an input formula…

Computational Complexity · Computer Science 2017-09-06 Pavel Pudlák , Dominik Scheder , Navid Talebanfard

In a $(k,2)$-Constraint Satisfaction Problem we are given a set of arbitrary constraints on pairs of $k$-ary variables, and are asked to find an assignment of values to these variables such that all constraints are satisfied. The…

Data Structures and Algorithms · Computer Science 2022-06-30 Or Zamir

Unstructured neural network pruning algorithms have achieved impressive compression rates. However, the resulting - typically irregular - sparse matrices hamper efficient hardware implementations, leading to additional memory usage and…

Schoening presents a simple randomized algorithm for (d,k)-CSP problems with running time (d(k-1)/k)^n poly(n). Here, d is the number of colors, k is the size of the constraints, and n is the number of variables. A derandomized version of…

Computational Complexity · Computer Science 2010-05-27 Dominik Scheder

The Kaczmarz algorithm is a popular solver for overdetermined linear systems due to its simplicity and speed. In this paper, we propose a modification that speeds up the convergence of the randomized Kaczmarz algorithm for systems of linear…

Numerical Analysis · Computer Science 2013-05-17 Hassan Mansour , Ozgur Yilmaz

We introduce and study a novel generalization of the classical Knapsack Problem (KP), called the Colored Knapsack Problem (CKP). In this problem, the items are partitioned into classes of colors and the packed items need to be ordered such…

Optimization and Control · Mathematics 2026-02-13 Fabio Ciccarelli , Alexander Helber , Erik Mühmer

We consider worst case time bounds for NP-complete problems including 3-SAT, 3-coloring, 3-edge-coloring, and 3-list-coloring. Our algorithms are based on a constraint satisfaction (CSP) formulation of these problems; 3-SAT is equivalent to…

Data Structures and Algorithms · Computer Science 2007-05-23 David Eppstein

We give a simpler derandomization of the best known $k$-SAT algorithm PPSZ [FOCS'97, JACM'05] for $k$-SAT with \emph{sub-exponential} number of solutions. The existing derandomization uses a complicated construction of small sample space,…

Computational Complexity · Computer Science 2020-01-22 S. Cliff Liu

We present randomized algorithms for some well-studied, hard combinatorial problems: the k-path problem, the p-packing of q-sets problem, and the q-dimensional p-matching problem. Our algorithms solve these problems with high probability in…

Data Structures and Algorithms · Computer Science 2010-07-08 Andreas Björklund , Thore Husfeldt , Petteri Kaski , Mikko Koivisto

Discrete probabilistic programs (DPPs) provide a highly expressive formalism for compactly defining arbitrary finite probabilistic models. This expressivity comes at a price: DPP inference is PSPACE-hard. In this work, we show that DPP…

Data Structures and Algorithms · Computer Science 2026-04-29 Benedikt Peterseim , Milan Lopuhaä-Zwakenberg

In this paper, by regarding the two-subspace Kaczmarz method [20] as an alternated inertial randomized Kaczmarz algorithm we present a new convergence rate estimate which is shown to be better than that in [20] under a mild condition.…

Numerical Analysis · Mathematics 2023-06-16 Songnian He , Ziting Wang , Qiao-Li Dong

Determinantal Point Processes (DPPs) are a family of probabilistic models that have a repulsive behavior, and lend themselves naturally to many tasks in machine learning where returning a diverse set of objects is important. While there are…

Statistics Theory · Mathematics 2017-03-03 John Urschel , Victor-Emmanuel Brunel , Ankur Moitra , Philippe Rigollet

We consider worst case time bounds for NP-complete problems including 3-SAT, 3-coloring, 3-edge-coloring, and 3-list-coloring. Our algorithms are based on a constraint satisfaction (CSP) formulation of these problems. 3-SAT is equivalent to…

Data Structures and Algorithms · Computer Science 2010-01-21 Richard Beigel , David Eppstein

In this paper we introduce "hybrid" Max 2-CSP formulas consisting of "simple clauses", namely conjunctions and disjunctions of pairs of variables, and general 2-variable clauses, which can be any integer-valued functions of pairs of boolean…

Data Structures and Algorithms · Computer Science 2009-06-22 Serge Gaspers , Gregory B. Sorkin

Determinantal point processes (DPPs) offer an elegant tool for encoding probabilities over subsets of a ground set. Discrete DPPs are parametrized by a positive semidefinite matrix (called the DPP kernel), and estimating this kernel is key…

Machine Learning · Computer Science 2015-10-12 Zelda Mariet , Suvrit Sra

The Kaczmarz algorithm is an iterative method that solves linear systems of equations. It stands out among iterative algorithms when dealing with large systems for two reasons. First, at each iteration, the Kaczmarz algorithm uses a single…

Numerical Analysis · Mathematics 2024-04-10 Inês A. Ferreira , Juan A. Acebrón , José Monteiro
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