Statistical Inference Under Constrained Selection Bias

Watch an 18-minute ACM conference talk exploring novel approaches to statistical inference when dealing with constrained selection bias, presented by researchers Santiago Cortés, Mateo Dulce, Carlos Patino, and Bryan Wilder as part of the Learning and Inference session, examining methodologies for handling biased data sampling in statistical analysis.