?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
The proliferation of information on the world wide web has made the personalization of this information space a necessity. One possible approach to web personalization is to mine ...
This paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. The proposed solution is based on random sampling and conceptual da...
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
We bring two rough-set-based clustering algorithms into the framework of partially supervised clustering. A mechanism of partial supervision relying on either qualitative or quanti...