publication

Print Demand Forecasting with Machine Learning at HP Inc.

HP Inc. replaced manual and statistical forecasting with a machine learning (LightGBM) model to improve demand prediction accuracy across 18,000+ print products. The model has been deployed enterprise-wide, with demonstrated business value and principles for scaling ML in large organizations.

End-to-End Inventory Prediction and Contract Allocation for Guaranteed Delivery Advertising

We proposed a novel end-to-end approach, the Neural Lagrangian Selling (NLS) model, to improve Guaranteed Delivery (GD) advertising by concurrently predicting ad impression inventory and optimizing contract allocation. The model incorporates a differentiable Lagrangian layer and a graph convolutional neural network to enable direct optimization of allocation regret and effective handling of various allocation targets and constraints.