382 citations · 534 across the 9 of their papers we have counts for
22 papers
Reinforcement Learning Under Algorithmic Triage
Eleni Straitouri, Adish Singla, Vahid Balazadeh Meresht +1
Methods to learn under algorithmic triage have predominantly focused on supervised learning settings where each decision, or prediction, is independent of each other. Under algorit…
Counterfactual Explanations in Sequential Decision Making Under Uncertainty
Stratis Tsirtsis, Abir De, Manuel Gomez-Rodriguez
Methods to find counterfactual explanations have predominantly focused on one step decision making processes. In this work, we initiate the development of methods to find counterfa…
Group Testing under Superspreading Dynamics
Stratis Tsirtsis, Abir De, Lars Lorch +1
Testing is recommended for all close contacts of confirmed COVID-19 patients. However, existing group testing methods are oblivious to the circumstances of contagion provided by co…
Large-scale randomized experiment reveals machine learning helps people learn and remember more effectively
Utkarsh Upadhyay, Graham Lancashire, Christoph Moser +1
Machine learning has typically focused on developing models and algorithms that would ultimately replace humans at tasks where intelligence is required. In this work, rather than r…
Classification Under Human Assistance
Abir De, Nastaran Okati, Ali Zarezade +1
Most supervised learning models are trained for full automation. However, their predictions are sometimes worse than those by human experts on some specific instances. Motivated by…
Decisions, Counterfactual Explanations and Strategic Behavior
Stratis Tsirtsis, Manuel Gomez-Rodriguez
As data-driven predictive models are increasingly used to inform decisions, it has been argued that decision makers should provide explanations that help individuals understand wha…