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Found 8 papers, 3 papers with code
Towards Graph Foundation Models for Personalization
In the realm of personalization, integrating diverse information sources such as consumption signals and content-based representations is becoming increasingly critical to build state-of-the-art solutions.
Generalized User Representations for Transfer Learning
In the second stage, downstream task-specific models leverage user representations via transfer learning instead of curating user features individually.
Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay
In this context, we study a content exploration task, which we formalize as a multi-armed bandit problem with delayed rewards.
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders
We address this challenge by aiming to learn the effect of a single-intervention from both observational data and sets of interventions.
Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing
We consider the task of sequencing tracks on music streaming platforms where the goal is to maximise not only user satisfaction, but also artist- and platform-centric objectives, needed to ensure long-term health and sustainability of the platform.
You Must Have Clicked on this Ad by Mistake! Data-Driven Identification of Accidental Clicks on Mobile Ads with Applications to Advertiser Cost Discounting and Click-Through Rate Prediction
We then estimate dwell time thresholds of accidental clicks from that component.
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking
There are many circumstances however where it is important to understand (i) why a model outputs a certain prediction on a given instance, (ii) which adjustable features of that instance should be modified, and finally (iii) how to alter such a prediction when the mutated instance is input back to the model.
Data Portraits: Connecting People of Opposing Views
However, users tend to connect with like-minded people and read agreeable information, a behavior that leads to group polarization.
Human-Computer Interaction Social and Information Networks H.5.2
