Feb. 6, 2024, 5:47 a.m. | Giacomo Pedretti John Moon Pedro Bruel Sergey Serebryakov Ron M. Roth Luca Buonanno Archit Gajjar

cs.LG updates on arXiv.org arxiv.org

Structured, or tabular, data is the most common format in data science. While deep learning models have proven formidable in learning from unstructured data such as images or speech, they are less accurate than simpler approaches when learning from tabular data. In contrast, modern tree-based Machine Learning (ML) models shine in extracting relevant information from structured data. An essential requirement in data science is to reduce model inference latency in cases where, for example, models are used in a closed …

contrast cs.lg data data science deep learning format images in-memory machine machine learning memory modern science speech tabular tabular data tree unstructured unstructured data

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