A recommendation system tracks past actions of a group of users to make recommendations to individual members of the group. The growth of computer-mediated marketing and commerce has led to increased interest in such systems. We introduce a simple analytical framework for recommendation systems, including a basis for defining the utility of such a system. We perform probabilistic analyses of al...

In this note we provide a simpler proof of a probabilistic analysis of the set cover problem given in [6]. We also prove these results using the language of high probability instead of using convergence in probability or convergence almost everywhere, making the previous results more precise.

Energy constraint is the biggest challenge in wireless sensor networks because the power supply of each sensor node is a battery that is not rechargeable or replaceable due to the applications of these networks. One of the successful methods for saving energy in these networks is clustering. It has caused that cluster-based routing algorithms are successful routing algorithm for these networks....

This thesis proposes a new method for unsupervised image clustering using probabilistic continuous models and information theoretic principles. Image clustering relates to content-based image retrieval systems. It enables the implementation of efficient retrieval algorithms and the creation of a user friendly interface to the database. The thesis presents a coherent theory for continuous probab...

This paper introduces a novel statistical latent class model for probabilistic grouping of distributional and histogram data. Adopting the Bayesian framework, we propose to perform annealed maximum a posteriori estimation to compute optimal clustering solutions. In order to accelerate the optimization process, an efficient multiscale formulation is developed. We present a prototypical applicati...

This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The algorithm is derived via a lowvariance asymptotic analysis of the Gibbs sampling algorithm for the DDPMM, and provides a hard clustering with convergence guarantees similar to those of the k-means alg...

The American Heart Association (AHA) has recommended a 12element questionnaire for pre-participation screening of athletes, in order to reduce and hopefully prevent sudden cardiac death in young athletes. This screening procedure is widely used throughout the United States, but its efficacy for discriminating Normal from Non-normal heart condition is unclear. As part of a larger study on cardio...

This paper presents a new method for providing probabilistic real-time guarantees to tasks scheduled through resource reservations. Previous work on probabilistic analysis of reservation-based schedulers is extended by improving the efficiency and robustness of the probability computation. Robustness is improved by accounting for a possibly incomplete knowledge of the distribution of the comput...