Nadav Golbandi

Budget-Constrained Item Cold-Start Handling in Collaborative Filtering Recommenders via Optimal Design

2015

It is well known that collaborative filtering (CF) based recommender systems provide better modeling of users and items associated with considerable rating history. The lack of historical ratings results in the user and the item …

TF-Ranking

2019

Learning-to-Rank deals with maximizing the utility of a list of examples presented to the user, with items of higher relevance being prioritized. It has several practical applications such as large-scale search, recommender systems, document summarization …

Position Bias Estimation for Unbiased Learning to Rank in Personal Search

2018

A well-known challenge in learning from click data is its inherent bias and most notably position bias. Traditional click models aim to extract the ‹query, document› relevance and the estimated bias is usually discarded after …