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IEEE/ICACT20260019 Slide.16        [Big Slide]       [YouTube]	Oral Presentation
	K-Nearest Neighbors (KNN) achieves high classification accuracy on the benchmark dataset. However, its distance-based inference requires comparison with multiple stored samples, resulting in high per-sample inference latency. This computational cost makes KNN unsuitable for real-time SmartNIC deployment, despite strong accuracy performance.

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