PROJECT TITLE :

Probabilistic Graphical Models on Multi-Core CPUs Using Java 8

ABSTRACT:

During this paper, we discuss software design issues connected to the event of parallel computational intelligence algorithms on multi-core CPUs, using the new Java eight purposeful programming options. In specific, we specialize in probabilistic graphical models (PGMs) and gift the parallelization of a collection of algorithms that accommodate inference and learning of PGMs from information. Specifically, most probability estimation, importance sampling, and greedy search for solving combinatorial optimization problems. Through these concrete examples, we tend to tackle the problem of defining economical knowledge structures for PGMs and parallel processing of same-size batches of information sets using Java 8 options. We tend to also provide straightforward techniques to code parallel algorithms that seamlessly exploit multicore processors. The experimental analysis, meted out using our open source AMIDST (Analysis of Massive Knowledge STreams) Java toolbox, shows the merits of the proposed solutions.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Millimeter-Wave Mobile Sensing and Environment Mapping Models, Algorithms and Validation ABSTRACT: One relevant research paradigm, particularly at mm-wave and sub-THz bands, is to integrate efficient connectivity,
PROJECT TITLE : GPCA A Probabilistic Framework for Gaussian Process Embedded Channel Attention ABSTRACT: It is common practice to employ channel attention mechanisms in a variety of visual tasks in order to achieve effective
PROJECT TITLE : Data Dissemination in VANETs Using Clustering and Probabilistic Forwarding Based on Adaptive Jumping Multi-Objective Firefly Optimization ABSTRACT: The dissemination of data within a VANETs network calls for
PROJECT TITLE : Learning Compact Features for Human Activity Recognition Via Probabilistic First-Take-All ABSTRACT: With the rise in popularity of mobile sensor technologies, smart wearable devices provide a once-in-a-lifetime
PROJECT TITLE : A Spatially Constrained Probabilistic Model for Robust Image Segmentation ABSTRACT: In probabilistic model based segmentation, the hidden Markov random field (HMRF) is used to describe the class label distribution

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry