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.
Results
Showing 1 to 9 of 9 for “"Probabilistic algorithms"”.
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Lifted First-Order Probabilistic Inference
… division in AI between logical symbolic and probabilistic reasoning approaches. While probabilistic models can deal well with inherent uncertainty in many real-world domains, they operate on a mostly propositional level. Logic systems, on the other hand, can deal with much richer …
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Towards Quality of Service and Fairness in Smart Grid Applications
… allocation mechanisms which are compared to new probabilistic algorithms. Both integrate user constraints (arrival time, departure time, and energy required) to manage the quality of service and fairness. In the queuing-based allocation mechanisms, electric vehicle charging requests are …
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Probabilistic Approximations of Matrix Decompositions for Inverse Problems
… inverse problems. This thesis also makes use of probabilistic algorithms for constructing approximate matrix decompositions. A probabilistic method of constructing locally accurate matrix approximations is introduced. A particular focus of this thesis is the Bayesian approximation error …
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On the performance of probabilistic flooding in wireless mobile ad hoc networks
… retransmission, collision and contention. Probabilistic flooding, where a node rebroadcasts a newly arrived one-to-all packet with some probability, p, was an early suggestion to reduce the broadcast storm problem. The first part of this thesis investigates the effects on the performance of …
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Reinforcing Reachable Routes
… spirit of the current backbone routing algorithms. We present the design and implementation of a new reachability algorithm that uses a model-based approach to achieve cost-sensitive multi-path forwarding. Performance assessment of the algorithm in various troublesome topologies shows …
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Probabilistic Continual Learning using Neural Networks
… be made online. In this thesis we present new algorithms for continual learning using neural networks. We use the probabilistic approach, which maintains a distribution over beliefs, naturally handling continual learning by recursively updating from priors to posteriors. Although previous work …
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Accelerating Probabilistic Computing with a Stochastic Processing Unit
… workload for computing systems than ever before. Probabilistic computing is a popular approach in statistical machine learning, which solves problems by iteratively generating samples from parameterized distributions. As an alternative to Deep Neural Networks, probabilistic computing provides …
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Applications of stochastic simulation in two-stage multiple comparisons with the best problem and time average variance constant estimation
In this dissertation, we study two problems. In the first part, we consider the two-stage methods for comparing alternatives using simulation. Suppose there are a finite number of alternatives to compare, with each alternative having an unknown parameter that is the basis for comparison. The …
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Real-time Traffic State Prediction: Modeling and Applications
… traffic modeling, computer vision and recursive probabilistic algorithms. Each developed method attempts to predict traffic state, including roadway travel times, for different prediction horizons. In total, the developed multi-tool framework produces traffic state prediction algorithms ranging …