activity
20162019
most citedDesign and Analysis of the NIPS 2016 Review Process

48 citations · 112 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2019★ 4 cited

Consequential Ranking Algorithms and Long-term Welfare

Behzad Tabibian, Vicenç Gómez, Abir De +2

Ranking models are typically designed to provide rankings that optimize some measure of immediate utility to the users. As a result, they have been unable to anticipate an increasi…

cs.LG2019★ 26 cited

Optimal Decision Making Under Strategic Behavior

Stratis Tsirtsis, Behzad Tabibian, Moein Khajehnejad +3

We are witnessing an increasing use of data-driven predictive models to inform decisions. As decisions have implications for individuals and society, there is increasing pressure o…

stat.ML2017★ 1 cited

Optimizing Human Learning

Behzad Tabibian, Utkarsh Upadhyay, Abir De +3

Spaced repetition is a technique for efficient memorization which uses repeated, spaced review of content to improve long-term retention. Can we find the optimal reviewing schedule…

cs.SI2017★ 1 cited

Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation

Jooyeon Kim, Behzad Tabibian, Alice Oh +2

Online social networking sites are experimenting with the following crowd-powered procedure to reduce the spread of fake news and misinformation: whenever a user is exposed to a st…

cs.DL2017★ 48 cited

Design and Analysis of the NIPS 2016 Review Process

Nihar B. Shah, Behzad Tabibian, Krikamol Muandet +2

Neural Information Processing Systems (NIPS) is a top-tier annual conference in machine learning. The 2016 edition of the conference comprised more than 2,400 paper submissions, 3,…

cs.SI2016★ 32 cited

Distilling Information Reliability and Source Trustworthiness from Digital Traces

Behzad Tabibian, Isabel Valera, Mehrdad Farajtabar +3

Online knowledge repositories typically rely on their users or dedicated editors to evaluate the reliability of their content. These evaluations can be viewed as noisy measurements…