Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"Approximate algorithm"”.
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Approximate inference : decomposition methods with applications to networks
… In this thesis, we present a new approximation algorithm for computing Maximum a Posteriori (MAP) and the log-partition function for arbitrary positive pair-wise MRF defined on a graph G. Our algorithm is based on decomposition of G into appropriately chosen small components; then computing …
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Bayesian learning for multi-agent coordination
… other agents. We used this insight to develop an approximate scalable algorithm applicable to our general model, in combination with adapting a number of existing approximation techniques, including state clustering.<br/>We examine the performance of this approximate algorithm on several cases of …
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Decomposition techniques for large-scale optimization in the supply chain
… times for the manufacturing plant model, an approximate decomposition technique is developed, applied to the plant model, and evaluated. The approximate algorithm developed in this work decomposes the problem into a three-level hierarchical structure and integrates a heuristic approach at two …
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Exploring the Landscape of Big Data Analytics Through Domain-Aware Algorithm Design
… the data analytics landscape with domain-aware approximate and incremental algorithm design. We propose three guidelines targeting three properties of big data for domain-aware big data analytics: (1) explore geometric and domain-specific properties of high dimensional data for succinct …
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Approximate Bayesian Modeling with Embedded Gaussian Processes
… front by studying asymptotic properties of the approximate posterior in GP surrogate models with generalized observations. We prove conditions and guarantees for consistent approximate inference in terms of posterior expectations and KL-divergence. Our convergence results provide a family of …
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Partitioning A Graph In Alliances And Its Application To Data Clustering
… and alliance cover sets. Finally, we present an approximate algorithm to discover alliances in a given graph. At each step, the algorithm finds a partition of the vertices into two alliances such that the alliances are strongest among all such partitions. The strength of an alliance is defined as …
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Network Based Approaches for Clustering and Location Decisions
… Next, a general purpose network clustering algorithm based on the clique relaxation concept of k-community is presented. A salient feature of this approach is that it does not use any prior information about the structure of the network. By defining a cluster as a k-community, the proposed …
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Stochastic sequential assignment problem
… Markov optimal policy are provided. An approximate algorithm is presented, and convergence of the approximate value function to the optimal value function is established under mild conditions. The second part of this thesis analyzes the limiting behavior of the SSAP as the number of …
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Energy Efficient Resource Allocation for Virtual Network Services with Dynamic Workload in Cloud Data Centers
… of the proposed model, we develop a heuristic algorithm for virtual network scheduling and mapping. In doing so, we specifically take the expected energy consumption at different times, virtual network operation and future migration costs, and a data center architecture into consideration. Our …