Monitoring network performance and status is a fundamental task for network operators as it directly impacts the quality of the offered services and hence user satisfaction. For this purpose a consolidated approach, which is largely adopted by network operators, is based on the so-called KPIs (key performance indicators). In this paper, we propose and discuss a set of KPIs to monitor network pe...

Reliability-Based Design Optimization (RBDO) involves evaluation of probabilistic constraints, which can be done in two different ways, the Reliability Index Approach (RIA) and the Performance Measure Approach (PMA). It has been reported in the literature that RIA yields instability for some problems but PMA is robust and efficient in identifying a probabilistic failure mode in the RBDO process...

This paper presents a rhythm recognition technique based on a probabilistic approach by utilizing generative model for timing information in expressive music performance. The problem of rhythm recognition including rhythm parsing and tempo tracking, is to retrieve information of rhythm and tempo from a sequence of observed note durations. Since performed note length deviates in real performance...

Image segmenting is one of the most important steps in movie and image processing and the machine vision applications. The evaluating methods of image segmenting that recently introduced. In this paper, we proposed a new formulation for the evaluation of image segmentation methods. In this strategy using probabilistic model that utilize the information of pixels (mean and variance) in each regi...

Collaborative Filtering attempts to make automatic taste recommendations by examing a large number of taste information. Methods for achieving Collaborative Filtering can be broadly categorized into model based, and memory based techniques. In this project, we review and implement three variants of Probabilistic Matrix Factorization, a model based Collaborative Filtering algorithm. We compare t...

Discovering Probabilistic Frequent Itemsets (PFI) is very challenging since algorithms designed for deterministic data are not applicable in probabilistic data. The problem is even more difficult for probabilistic data streams where massive frequent updates need to be taken into account while respecting data stream constraints. In this paper, we propose FEMP (Fast and Exact Mining of Probabilis...