Results 31 to 40 of about 3,624,996 (285)
Optimal Algorithms for Distributed Optimization
CoRR, 2017 In this paper, we study the optimal convergence rate for distributed convex optimization problems in networks. We model the communication restrictions imposed by the network as a set of affine constraints and provide optimal complexity bounds for four different setups, namely: the function $F(\xb) \triangleq \sum_{i=1}^{m}f_i(\xb)$ is strongly convex ...
César A. Uribe +3 more
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A general decomposition theory for the 1-2-3 Conjecture and locally irregular decompositions [PDF]
Discrete Mathematics & Theoretical Computer Science, 2019 How can one distinguish the adjacent vertices of a graph through an edge-weighting? In the last decades, this question has been attracting increasing attention, which resulted in the active field of distinguishing labellings.
Olivier Baudon +7 more
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Improved approximation algorithms for optimization problems in graphs with superlogarithmic treewidth [PDF]
, 2003 In this paper we present two novel generic schemes for approximation algorithms for optimization to partial k-trees. Our first scheme yields deterministic polynomialtime algorithms achieving typically an approximation factor of k/ log n, where k
Chlebikova, Janka +14 more
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Optimization of the Complex-RFM optimization algorithm
Optimization and Engineering, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Persson, Johan, Ölvander, Johan
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An evolutionary algorithm for multi-objective optimization of freshwater consumption in textile dyeing industry [PDF]
PeerJ Computer Science, 2022 Optimization is challenging even after numerous multi-objective evolutionary algorithms have been developed. Most of the multi-objective evolutionary algorithms failed to find out the best solutions spread and took more fitness evolution value to find ...
Ihsan Elahi +5 more
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Optimization of machine learning algorithms for proteomic analysis using topsis
Журнал інженерних наук, 2022 The present study focuses on a new application of the TOPSIS method for the optimization of machine learning algorithms, supervised neural networks (SNN), the quick classifier (QC), and genetic algorithm (GA) for proteomic analysis.
Javanbakht T., Chakravorty S.
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Raccoon Optimization Algorithm [PDF]
IEEE Access, 2019 Population-based meta-heuristic is a high-level method intended to provide sufficient solution for problems with incomplete information among a massive volume of solutions. However, it does not guarantee to attain global optimum in a reasonable time.
Sina Zangbari Koohi +3 more
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Leanness Computation: Small Values and Special Graph Classes [PDF]
Discrete Mathematics & Theoretical Computer ScienceLet u and v be vertices in a connected graph G = (V, E). For any integer k such that 0 ≤ k ≤ dG (u, v), the k-slice Sk (u, v) contains all vertices x on a shortest uv-path such that dG (u, x) = k.
David Coudert +2 more
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Pushing Vertices to Make Graphs Irregular [PDF]
Discrete Mathematics & Theoretical Computer ScienceIn connection with the so-called 1-2-3 Conjecture, we introduce and study a new problem related to proper labellings. In the regular problem, proper labellings of graphs are designed by assigning strictly positive labels to the edges so that any two ...
Julien Bensmail +2 more
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Crayfish optimization algorithm
Artificial Intelligence Review, 2023 This paper proposes a meta heuristic optimization algorithm, called Crayfish Optimization Algorithm (COA), which simulates crayfish’s summer resort behavior, competition behavior and foraging behavior. The three behaviors are divided into three different stages to balance the exploration and exploitation of algorithm. The three stages are summer resort
Heming Jia +3 more
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