Search Results - "Adaptive randomized algorithms"

Randomized algorithms for the approximations of Tucker and the tensor train decompositions by Che, Maolin, Wei, Yimin

“… The main purpose of this paper is to design adaptive randomized algorithms for computing the approximate tensor decompositions…”
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Bounds for the Number of Tests in Non-Adaptive Randomized Algorithms for Group Testing by Bshouty, Nader H, Haddad, George, Haddad-Zaknoon, Catherine A

“…We study the group testing problem with non-adaptive randomized algorithms. Several models have been discussed in the literature to determine how to randomly choose the tests. For a model \({\cal M}\), let \(m_{\cal M}(n,d…”
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Adaptive randomized algorithms for validation and analysis of complex systems by Kim, Jongwoo

“…This thesis addresses the problem of validating software-enabled controllers for complex systems with dynamic constraints. In such complex systems, the…”
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An adaptive and diversified vehicle routing approach to reducing the security risk of cash‐in‐transit operations by Bozkaya, Burcin, Salman, F. Sibel, Telciler, Kaan

“…We consider the route optimization problem of transporting valuables in cash‐in‐transit (CIT) operations. The problem arises as a rich variant of the…”
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Non-Adaptive Randomized Algorithm for Group Testing by Bshouty, Nader H, Diab, Nuha, Kawar, Shada R, Shahla, Robert J

“…We study the problem of group testing with a non-adaptive randomized algorithm in the random incidence design (RID…”
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Adaptive randomized algorithm for finding eigenvector of stochastic matrix with application to PageRank by Nazin, A., Polyak, B.

“… We propose a novel adaptive randomized algorithm and provide an explicit upper bound for its rate of convergence O(¿(lnN/n…”
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Improved lower bound for estimating the number of defective items by Bshouty, Nader H.

“… For any given constant j , any non-adaptive randomized algorithm that, with probability at least 2/3, estimates the number of defective items…”
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A tight lower bound on non-adaptive group testing estimation by Bshouty, Nader H., Cheung, Tsun-Ming, Harcos, Gergely, Hatami, Hamed, Ostuni, Anthony

“… We show that any non-adaptive randomized algorithm that estimates the value of d within a constant factor requires Ω(logn) queries…”
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An adaptive randomized and secured approach against adversarial attacks by Dhamija, Lovi, Garg, Urvashi

“…With the rising trends and use of machine learning algorithms for classification and regression tasks, deep learning has been widely accepted in the Cyber and…”
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Randomized Local Model Order Reduction by Buhr, Andreas, Smetana, Kathrin

“…In this paper we propose local approximation spaces for localized model order reduction procedures such as domain decomposition and multiscale methods. Those…”
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A Note on Rounding Matchings in General Graphs by Dudeja, Aditi

“…In this note, we revisit the rounding algorithm of Wajc. Wajc gave a fully-adaptive randomized algorithm that rounds a dynamic fractional matching…”
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Incremental SSSP for Sparse Digraphs Beyond the Hopset Barrier by Kyng, Rasmus, Meierhans, Simon, Maximilian Probst Gutenberg

“… For sparse graphs, Chechik and Zhang [SODA'21] recently presented a deterministic \(\tilde{O}(m^{5/3})\) algorithm, and an adaptive randomized algorithm with run-time…”
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Learning Multiple Secrets in Mastermind by Prabhu, Milind, Woodruff, David

“…\) while making at most \(\exp(\tilde{O}(\sqrt{d \log n}))\) queries. Furthermore, we show that any \(r\)-round adaptive randomized algorithm that learns…”
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Graph Reconstruction via MIS Queries by Konrad, Christian, O'Sullivan, Conor, Traistaru, Victor

“…In the Graph Reconstruction (GR) problem, a player initially only knows the vertex set \(V\) of an input graph \(G=(V, E)\) and is required to learn its set of…”
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A tight lower bound on non-adaptive group testing estimation by Bshouty, Nader H, Cheung, Tsun-Ming, Harcos, Gergely, Hatami, Hamed, Ostuni, Anthony

“… We show that any non-adaptive randomized algorithm that estimates the value of \(d\) within a constant factor requires \(\Omega(\log n)\) queries…”
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Randomized algorithms for computing the tensor train approximation and their applications by Che, Maolin, Wei, Yimin, Hong, Yan

“… Thirdly, we deduce a new deterministic strategy to estimate the desired TT-rank with a given tolerance and another adaptive randomized algorithm that finds a low TT-rank representation satisfying…”
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A Tight Lower Bound of \(\Omega(\log n)\) for the Estimation of the Number of Defective Items by Bshouty, Nader H, Harcos, Gergely

“… Employing this new method, we can prove the following result. Any non-adaptive randomized algorithm that, for any set of defective items…”
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Improved Lower Bound for Estimating the Number of Defective Items by Bshouty, Nader H

“…\), any non-adaptive randomized algorithm that, for any set of defective items \(I\), with probability at least \(2/3…”
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Butterfly factorization via randomized matrix-vector multiplications by Liu, Yang, Xing, Xin, Guo, Han, Michielssen, Eric, Ghysels, Pieter, Xiaoye Sherry Li

“…This paper presents an adaptive randomized algorithm for computing the butterfly factorization of a \(m\times n\) matrix with \(m\approx n…”
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On the Gap Between Strict-Saddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation by Simchowitz, Max, Ahmed El Alaoui, Recht, Benjamin

“…}\). We show that for a small constant \(\epsilon\), any adaptive, randomized algorithm which can find a unit vector \(\widehat{v}\) for which \(\widehat{v}^{\top}M\widehat{v} \ge (1-\epsilon)\|M…”
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