Optimization Matters More Than Estimation This Research Card shows that in large-scale recommendation systems, like those used at Criteo, focusing on how we optimize algorithms is more impactful than trying to perfectly estimate outcomes. By using simpler, more stable training objectives, we can achieve better click-through rates, faster experimentation, and more scalable performance across millions…