4 papers
When Offline Evaluation Misleads: A Diagnostic Protocol for Reward and Policy Selection in Delayed-Feedback Contextual Bandits
Sang Su Lee, Vineeth Loganathan, Shishir Dash +1
Personalizing marketing messages with contextual multi-armed bandits (CMABs) drives real business value, yet the objective that ultimately matters - a downstream conversion - is ob…
Certifying What Helps Customer-Return Timing: A Screen-and-Confirm Test for Conditioning Signals, and Why Decay Is Nearly Enough
Sang Su Lee, Vineeth Loganathan, Shishir Dash +1
Practitioners enrich customer-return models with ever more signals (lifetime value, category, recency/frequency, calendar, geography), and the temporal-point-process (TPP) literatu…
Beyond the Hype: Embeddings vs. Prompting for Multiclass Classification Tasks
Marios Kokkodis, Richard Demsyn-Jones, Vijay Raghavan
Are traditional classification approaches irrelevant in this era of AI hype? We show that there are multiclass classification problems where predictive models holistically outperfo…
Dynamic Synthetic Controls vs. Panel-Aware Double Machine Learning for Geo-Level Marketing Impact Estimation
Sang Su Lee, Vineeth Loganathan, Vijay Raghavan
Accurately quantifying geo-level marketing lift in two-sided marketplaces is challenging: the Synthetic Control Method (SCM) often exhibits high power yet systematically under-esti…