Here is a blueprint for architecting real-time systems that scale without sacrificing speed. A common mistake I see in early-stage personalization teams is trying to rank every item in the catalog in ...
Abstract: 1 Today, advances in scientific and embedded computing and the incredible proliferation of machine learning algorithms take advantage of specialized hardware accelerators to provide ...
Abstract: Sparsity is becoming arguably the most critical dimension to explore for efficiency and scalability as deep learning models grow significantly larger. Particularly, pruning is a common ...
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