3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 3 cited
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks
Claudia V. Roberts, Ehtsham Elahi, Ashok Chandrashekar
We evaluate two popular local explainability techniques, LIME and SHAP, on a movie recommendation task. We discover that the two methods behave very differently depending on the sp…
cs.IR2020★ 1 cited
Learning Representations of Hierarchical Slates in Collaborative Filtering
Ehtsham Elahi, Ashok Chandrashekar
We are interested in building collaborative filtering models for recommendation systems where users interact with slates instead of individual items. These slates can be hierarchic…
stat.ML2016
A Nonparametric Latent Factor Model For Location-Aware Video Recommendations
Ehtsham Elahi
We are interested in learning customers' video preferences from their historic viewing patterns and geographical location. We consider a Bayesian latent factor modeling approach fo…