Tag: Model Compression

Architectures of Efficiency: A Comprehensive Analysis of Model Compression via Distillation, Pruning, and Quantization

Posted on by uplatzblog

Section 1: The Imperative for Model Compression in the Era of Large-Scale AI 1.1 The Paradox of Scale in Modern AI The contemporary landscape of artificial intelligence is dominated by Read More …

The Evolution of Knowledge Distillation: A Survey of Advanced Teacher-Student Training Paradigms

Posted on by uplatzblog

Introduction: Beyond Classical Knowledge Distillation Knowledge Distillation (KD) has emerged as a cornerstone technique in machine learning, fundamentally addressing the tension between model performance and deployment efficiency.1 As deep neural Read More …