The feature hashing algorithm introduced by Weinberger et al. (2009) is a popular dimensionality reduction that compresses high dimensional data points into low closely approximate the pairwise inner product. This has been used in many fundamental machine learning applications such as model compression (Chen 2015), spam classification (Weinberger 2009), compressing text classifiers (Joulin 2016...

Modern neural networks have revolutionized the fields of computer vision (CV) and Natural Language Processing (NLP). They are widely used for solving complex CV tasks NLP such as image classification, generation, machine translation. Most state-of-the-art over-parameterized require a high computational cost. One straightforward solution is to replace layers with their low-rank tensor approximat...

In a complex manufacturing system such as the multistage system, maintaining quality of products becomes challenging task. It is due to interconnectivity and dependency factors that can affect final product. With increasing availability data, Machine Learning (ML) approaches are applied assess predict quality-related issues. this paper, several ML algorithms, including feature reduction/selecti...