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Titlebook: Optimization and Applications; 14th International C Nicholas Olenev,Yuri Evtushenko,Vlasta Malkova Conference proceedings 2023 The Editor(s

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Algorithms for Euclidean-Regularised Optimal Transport Variance Reduction algorithms. Furthermore, the paper compares the practical efficiency of these methods and their counterparts when applied to the entropy-regularized Optimal Transport problem. This comparison is conducted through numerical experiments carried out on the MNIST dataset.
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One Segregation Problem for the Sum of Two Quasiperiodic Sequencesch to this problem leads to solving an unexplored discrete optimization problem. A polynomial-time algorithm that guarantees the optimal solution to this optimization problem is proposed. Additionally, there are some examples of numerical simulation for illustration.
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Real Acceleration of Communication Process in Distributed Algorithms with Compressionompression. In particular, we describe the real speedup achieved by compression, analyze how much it makes sense to compress information, and present an adaptive way to select the power of compression depending on unknown or changing parameters of the communication process.
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Reliable Production Process Design Problem: Compact MILP Model and ALNS-Based Primal Heuristicms. In order to find (close to) optimal solutions of the problem in question efficiently, we propose a compact Mixed Integer Linear Program (MILP) model and an Adaptive Large Neighborhood Search (ALNS) based primal heuristic. Results of their extensive numerical evaluation on top of the Gurobi branc
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itik wird dieser Trend meist mit dem Ruf nach Verhandlungen aller „stakeholders“ begründet und begleitet, was — je nach Kontext — als zivilere, effektivere, effizientere oder besser akzeptierte Form der Problembewältigung erscheint. In der Politikwissenschaft ist der Wandel von Politikformen hin zu
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