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Related papers: A Tight Lower Bound for Compact Set Packing

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We consider the online bin packing problem under the advice complexity model where the 'online constraint' is relaxed and an algorithm receives partial information about the future requests. We provide tight upper and lower bounds for the…

Data Structures and Algorithms · Computer Science 2013-12-24 Joan Boyar , Shahin Kamali , Kim S. Larsen , Alejandro López-Ortiz

We prove tight lower bounds for the following variant of the counting problem considered by Aaronson, Kothari, Kretschmer, and Thaler (2020). The task is to distinguish whether an input set $x\subseteq [n]$ has size either $k$ or…

Quantum Physics · Physics 2024-05-08 Aleksandrs Belovs , Ansis Rosmanis

The squashed entanglement is a widely used entanglement measure that has many desirable properties. However, as it is based on an optimization over extensions of arbitrary dimension, one drawback of this measure is the lack of good…

Quantum Physics · Physics 2022-03-08 Hamza Fawzi , Omar Fawzi

In this paper we prowide lower bounds on the complexity of the DNF exception problem for short exception lists and hypercube covering problem. The method proposed is based on the relaxation of the initial problem to a certain linear…

Combinatorics · Mathematics 2015-01-13 Yura Maximov

This work aims to study and explore the use of Gene Expression Programming (GEP) in solving the on-line Bin-Packing problem. The main idea is to show how GEP can automatically find acceptable heuristic rules to solve the problem efficiently…

Neural and Evolutionary Computing · Computer Science 2020-01-28 Najla Akram Al-Saati

We consider (closed neighbourhood) packings and their generalization in graphs called limited packings. A vertex set X in a graph G is a k-limited packing if for any vertex $v\in V(G)$, $\left|N[v] \cap X\right| \le k$, where $N[v]$ is the…

Discrete Mathematics · Computer Science 2014-07-08 Andrei Gagarin , Vadim Zverovich

In this paper, we will give an improvement on the lower bound for the counterfeit coins problem in the case that the number of false coins is unknown in advance

Combinatorics · Mathematics 2010-04-27 An-Ping Li , Hagen von Eitzen

In this paper, we introduce a general framework for fine-grained reductions of approximate counting problems to their decision versions. (Thus we use an oracle that decides whether any witness exists to multiplicatively approximate the…

Data Structures and Algorithms · Computer Science 2020-11-25 Holger Dell , John Lapinskas

Kernelization---a mathematical key concept for provably effective polynomial-time preprocessing of NP-hard problems---plays a central role in parameterized complexity and has triggered an extensive line of research. This is in part due to a…

Computational Complexity · Computer Science 2017-08-28 Henning Fernau , Till Fluschnik , Danny Hermelin , Andreas Krebs , Hendrik Molter , Rolf Niedermeier

A kernel based procedure for correcting experimental data for distortions due to the finite resolution and limited detector acceptance is presented. The unfolding problem is known to be an ill-posed problem that can not be solved without…

Data Analysis, Statistics and Probability · Physics 2012-09-19 N. D. Gagunashvili , M. Schmelling

This paper discusses the problem of weakly supervised classification, in which instances are given weak labels that are produced by some label-corruption process. The goal is to derive conditions under which loss functions for weak-label…

Machine Learning · Statistics 2021-06-14 Shuhei M. Yoshida , Takashi Takenouchi , Masashi Sugiyama

A minimum dominating set in a graph is a minimum set of vertices such that every vertex of the graph either belongs to it, or is adjacent to one vertex of this set. This mathematical object is of high relevance in a number of applications…

Artificial Intelligence · Computer Science 2018-08-30 Mayra Albuquerque , Thibaut Vidal

In this technical note we describe a pair of results on heterotic compactifications. First, we give an example demonstrating that the usual statement of the anomaly-freedom constraint for perturbative heterotic compactifications (meaning,…

High Energy Physics - Theory · Physics 2014-11-18 E. Sharpe

Squashed entanglement is a promising entanglement measure that can be generalized to multipartite case, and it has all of the desirable properties for a good entanglement measure. In this paper we present computable lower bounds to evaluate…

Quantum Physics · Physics 2009-08-04 Wei Song

The element distinctness problem takes as input a list $I$ of $n$ values from a totally ordered universe and the goal is to decide whether $I$ contains any duplicates. It is a well-studied problem with a classical worst-case $\Omega(n \log…

Data Structures and Algorithms · Computer Science 2025-11-06 Ivor van der Hoog , Eva Rotenberg , Daniel Rutschmann

We prove a sup norm bound on the real-analytic Eisenstein series, of the form $E(z, 1/2 + iT) \ll T^{3/8 + \varepsilon}$, uniformly for $z$ in a fixed compact subset of $\mathbb{H}$.

Number Theory · Mathematics 2020-08-17 Matthew P. Young

We prove a tight lower bound for the exponent $\rho$ for data-dependent Locality-Sensitive Hashing schemes, recently used to design efficient solutions for the $c$-approximate nearest neighbor search. In particular, our lower bound matches…

Data Structures and Algorithms · Computer Science 2015-07-16 Alexandr Andoni , Ilya Razenshteyn

A flaw in the greedy approximation algorithm proposed by Zhang et al. for minimum connected set cover problem is corrected, and a stronger result on the approximation ratio of the modified greedy algorithm is established. The results are…

Data Structures and Algorithms · Computer Science 2015-03-19 Wei Ren , Qing Zhao

The at-most-k constraint is ubiquitous in combinatorial problems, and numerous SAT encodings are available for the constraint. Prior experiments have shown the competitiveness of the sequential-counter encoding for k $>$ 1, and have…

Logic in Computer Science · Computer Science 2020-05-14 Neng-Fa Zhou

This paper concerns the problem of 1-bit compressed sensing, where the goal is to estimate a sparse signal from a few of its binary measurements. We study a non-convex sparsity-constrained program and present a novel and concise analysis…

Machine Learning · Computer Science 2020-07-10 Jie Shen
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