<ul><li>Recent research introduces RETENTION, an end-to-end framework to reduce CAM capacity requirement for tree-based model inference.</li><li>RETENTION includes an iterative pruning algorithm with a novel criterion and a tree mapping scheme with innovative data placement strategies.</li><li>Implementation of the tree mapping scheme alone achieves significantly improved space efficiency.</li><li>The full RETENTION framework results in a substantial improvement in CAM capacity requirement with minimal accuracy loss, offering a resource-efficient approach for tree-based model acceleration.</li></ul>

RETENTION: Resource-Efficient Tree-Based Ensemble Model Acceleration with Content-Addressable Memory

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