Optimizing Machine Learning Models with Data-level Approximate Computing: The Role of Diverse Sampling, Precision Scaling, Quantization and Feature Selection Strategies

Pilot-Verifi ed Mismatch-Robust Hybrid Digital Backpropagation with SafePhase-Equivariant FLNN Correction for Hardware-Impaired Coherent WDM Systems

An Optimized Twofold LUT Architecture for Fast Function Approximation

Group-Based Sample Partitioning kNN: A Computationally Efficient kNN Algorithm for Resource-Constrained Environments

Low-power and low-latency hardware implementation of approximate hyperbolic and exponential functions for embedded system applications

Approximate computing: Concepts, architectures, challenges, applications, and future directions