2k citations · 3.4k across the 66 of their papers we have counts for
18 papers · 1 filter
Scalable Transfer Evolutionary Optimization: Coping with Big Task Instances
Mojtaba Shakeri, Erfan Miahi, Abhishek Gupta +1
In today's digital world, we are faced with an explosion of data and models produced and manipulated by numerous large-scale cloud-based applications. Under such settings, existing…
The Gray Rhino of Pandemic Preparedness: Proactive digital, data, and organizational infrastructure to help humanity build resilience in the face of pandemics
Abhishek Gupta
COVID-19 has exposed glaring holes in our existing digital, data, and organizational practices. Researchers ensconced in epidemiological and human health work have repeatedly point…
Providing Actionable Feedback in Hiring Marketplaces using Generative Adversarial Networks
Daniel Nemirovsky, Nicolas Thiebaut, Ye Xu +1
Machine learning predictors have been increasingly applied in production settings, including in one of the world's largest hiring platforms, Hired, to provide a better candidate an…
CounteRGAN: Generating Realistic Counterfactuals with Residual Generative Adversarial Nets
Daniel Nemirovsky, Nicolas Thiebaut, Ye Xu +1
The prevalence of machine learning models in various industries has led to growing demands for model interpretability and for the ability to provide meaningful recourse to users. F…
Report prepared by the Montreal AI Ethics Institute In Response to Mila's Proposal for a Contact Tracing App
Allison Cohen, Abhishek Gupta
Contact tracing has grown in popularity as a promising solution to the COVID-19 pandemic. The benefits of automated contact tracing are two-fold. Contact tracing promises to reduce…
Adversary Agnostic Robust Deep Reinforcement Learning
Xinghua Qu, Yew-Soon Ong, Abhishek Gupta +1
Deep reinforcement learning (DRL) policies have been shown to be deceived by perturbations (e.g., random noise or intensional adversarial attacks) on state observations that appear…