Tagged
Multi-Task Learning
Recommendation Systems (9): Multi-Task Learning and Multi-Objective Optimization
How real recommenders juggle clicks, conversions, watch time and revenue at once. Shared-Bottom, ESMM, MMoE, PLE explained from first principles, with PyTorch code, loss-balancing strategies and the gradient-conflict …
Transfer Learning (6): Multi-Task Learning
Train one model on multiple tasks simultaneously. Covers hard vs. soft parameter sharing, gradient conflicts (PCGrad, GradNorm, CAGrad), auxiliary task design, and a complete multi-task framework with dynamic weight …