Tensor-based Approach to Big Data Processing and Machine Learning

 We present an approach to tensor compression, decomposition and processing algorithms on the top of them. Our implementation uses the popular scalable data processing framework Apache Parquet to effectively store data. This library does not directly store tensors as native data types, but we slightly changed the implementation for our purpose using its specific data storage format and extending it with additional compression. We summarize the performance of tensor storage as well as the effectiveness of multiple machine learning methods and their hyperparameter tuning.
 

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