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constraint-driven selection 1deployment constraints 1inference optimization 1model compression 1multi-objective engineering 1

From the 1 of 1 linked paper with an AI index.

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1 paper

cs.LG2026

Constraint-Driven Model Optimization: An Industry Framework for Selecting Compression and Acceleration Techniques in Modern Machine Learning Systems

Dhruv Shivkant, Saket Mohanty, Utkarsh Wadhwa +1

The paper introduces a constraint-driven, multi-objective framework for selecting model compression and acceleration techniques based on deployment constraints such as latency, mem…