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Academic Spotlight: VR Supermarket- a Virtual Reality Online Shopping Platform with a Dynamic Recommendation System

HPCC Systems has a robust Academic Program that collaborates with colleges, universities, high schools and institutions of higher learning around the world.

One such collaboration with the Rashtreeya Vidyalaya College of Engineering (RVCE) in Bengaluru, India, has resulted in a new publication:

The Hidden World of Unicode - From Text to Emojis

When we use our smart phones, we are used to texting each other using our own native language, often a second language (more and more people are multi-lingual), and something newer than text: emojis. Not only do smart phones have to deal with all this, servers, databases, text processors, and even machine learning have to be able to navigate this strange world of modern text. But how do they do it?

Random Fourier Features accelerated Gaussian Process Regressor

Gaussian process regression is a powerful machine learning method to solve non-linear regression problems. However, because of the intensive computation, Gaussian process regression is not suitable for large-scale machine learning problems. Fortunately, researchers developed approximation methods to get a solution arbitrarily close as the original Gaussian process more rapidly and with better scaling. In this post, a Random Fourier Features accelerated Gaussian process regressor will be introduced.

Academic Spotlight: Hybrid Density-based Adaptive Clustering using Gaussian Kernel and Grid Search

HPCC Systems has a robust Academic Program that collaborates with colleges, universities, high schools and institutions of higher learning around the world. One such collaboration with the Rashtreeya Vidyalaya College of Engineering (RVCE) in Bengaluru, India, has resulted in a new publication: Hybrid Density-based Adaptive Clustering using  Gaussian Kernel and Grid Search, published by IEEE Xplore®

Understanding Natural Language

There is a big difference between recognizing natural language and understanding it. Machine Learning has given the impression that it has or will solve natural language processing and that dictionaries, syntax, and all the traditional trappings of linguistics are simply not needed. This could not be further from the truth. The money lies in understanding and until now, understanding has been impossible to achieve.

Update - Integrating Prior Knowledge with Biomedical Natural Language Processing

Jingqing Zhang, Ph.D. (HiPEDS) candidate at Department of Computing, Imperial College London, London, UK has done incredible work in the areas of biomedical natural language processing, traffic prediction, and text classification. Jingqing is nearing the end of his doctoral studies, and this blog highlights his latest HPCC Systems community-sponsored research project.
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