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per algorithm » deer algorithm (Expand Search), rd algorithm (Expand Search), search algorithm (Expand Search)
elements per » elementi per (Expand Search), elements _ (Expand Search)
5a algorithm » rd algorithm (Expand Search), jaya algorithm (Expand Search), _ algorithms (Expand Search)
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1
A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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2
A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
Published 2010“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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3
Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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4
Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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5
A Framework for Predictive Modeling in Sustainable Projects
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6
Correlation Clustering with Overlaps
Published 2020“…We present a heuristic algorithm and a semi-exact algorithm for the Multi-Parameterized Cluster Editing with Vertex Splitting problem. …”
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7
Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
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8
Multidimensional Gains for Stochastic Approximation
Published 2019“…The proposed algorithms here aim for per-iteration minimization of the mean square estimate error. …”
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9
Machine Learning-Based Approach for EV Charging Behavior
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10
On the complexity of multi-parameterized cluster editing
Published 2017“…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
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