activity
20172022
most citedGlowing Experience or Bad Trip? A Quantitative Analysis of User Reported Drug Experiences on Erowid.org

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SI20221 cited

Glowing Experience or Bad Trip? A Quantitative Analysis of User Reported Drug Experiences on Erowid.org

Angelina Mooseder, Momin M. Malik, Hemank Lamba +3

Erowid.org is a website dedicated to documenting information about psychoactive substances, with over 36,000 user-submitted drug Experience Reports. We study the potential of these…

cs.LG2021

An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings

Hemank Lamba, Kit T. Rodolfa, Rayid Ghani

Applications of machine learning (ML) to high-stakes policy settings -- such as education, criminal justice, healthcare, and social service delivery -- have grown rapidly in recent…

cs.LG2020

Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy

Kit T. Rodolfa, Hemank Lamba, Rayid Ghani

Growing use of machine learning in policy and social impact settings have raised concerns for fairness implications, especially for racial minorities. These concerns have generated…

cs.SI2019

Driving The Last Mile: Characterizing and Understanding Distracted Driving Posts on Social Networks

Hemank Lamba, Shashank Srikanth, Dheeraj Reddy Pailla +3

In 2015, 391,000 people were injured due to distracted driving in the US. One of the major reasons behind distracted driving is the use of cell-phones, accounting for 14% of fatal…

cs.AI2017

Item Recommendation with Evolving User Preferences and Experience

Subhabrata Mukherjee, Hemank Lamba, Gerhard Weikum

Current recommender systems exploit user and item similarities by collaborative filtering. Some advanced methods also consider the temporal evolution of item ratings as a global ba…