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Probabilistic latent semantic analysis (PLSA) has been widely used in the machine learning community. However, the original PLSAs are not capable of modeling real-valued observations and usually have severe problems with over fitting. To address both issues, we propose a novel, regularized Gaussian PLSA (RG-PLSA) model that combines Gaussian PLSAs and hierarchical Gaussian mixture models (HGMM). We...
This paper introduces PartitionSim, a parallel simulator for future thousand-core processors. The purpose of PartitionSim is to improve the simulation performance of many-core architectures at the expense of little accuracy sacrifice. To achieve this goal, we propose a novel technique: timing partition. Timing partition is based on such an observation: in a target system, interacting components communicate...
this paper addresses the workload partition strategies in simulating many-core architectures. The key observation behind this paper is: compared to multicore, manycore features with more non-uniform memory access and unpredictable network traffic; these features degrade simulation speed and accuracy of parallel discrete event simulators (PDES) in cases of static workload partition schemes. Based on...
How to effectively monitor water quality of Coastal and inland waters by optical remote sensing has always been a difficulty. This study develops a neural network model to improve the accuracy in monitoring water quality of Lake Taihu, China, a large shallow subtropical lake. A three-layer back-propagation neural network is built up to estimate concentrations of chlorophyll-a, total suspended matter...
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