Alex Beutel

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection

2016

Review fraud is a pervasive problem in online commerce, in which fraudulent sellers write or purchase fake reviews to manipulate perception of their products and services. Fake reviews are often detected based on several signs, …

OEC: Open-Ended Classification for Future-Proof Link-Fraud Detection.

2017 · arXiv (Cornell University)

When tasked to find fraudulent social network users, what is a practitioner to do? Traditional classification can lead to poor generalization and high misclassification given few and possibly biased labels. We tackle this problem by …

Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals

2023 · arXiv (Cornell University)

Counterfactual Data Augmentation (CDA) is a commonly used technique for improving robustness in natural language classifiers. However, one fundamental challenge is how to discover meaningful counterfactuals and efficiently label them, with minimal human labeling cost. …

Recurrent Recommender Networks

2017

Recommender systems traditionally assume that user profiles and movie attributes are static. Temporal dynamics are purely reactive, that is, they are inferred after they are observed, e.g. after a user's taste has changed or based …

Latent Cross

2018

The success of recommender systems often depends on their ability to understand and make use of the context of the recommendation request. Significant research has focused on how time, location, interfaces, and a plethora of …