Grouping features in big dimensionality - Zhai, Yiteng (2016)
To date, the world continues to generate quintillion bytes of data daily, leading to the pressing needs for new efforts in dealing with the grand challenges brought by Big Data. When talking about big data, there is a growing consensus among the computational intelligence communities that data volume presents an immediate challenge pertaining to the scalability issue. Note that, when addressing volume in Big Data analytics, researchers have largely taken a one-sided study which refers to the "Big Instance Size" factor of the data. The flip side of volume which is the "Big Dimensionality" factor of big data, on the other hand, has received much less attention. A motivating example is related with cell phone manufacturing industry. It is worth noting that presently one can easily enjoy up to an extremely high resolution of 41-megapixels on the pictures taken, which is 400 times more than the 0.11-megapixels almost a decade ago. As a pixel based feature representation, this will explicitly translate to 41 million features.