19 citations · 53 across the 13 of their papers we have counts for
3 papers · 1 filter
Counterfactual Generation Under Confounding
Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma +1
A machine learning model, under the influence of observed or unobserved confounders in the training data, can learn spurious correlations and fail to generalize when deployed. For…
The Counterfactual-Shapley Value: Attributing Change in System Metrics
Amit Sharma, Hua Li, Jian Jiao
Given an unexpected change in the output metric of a large-scale system, it is important to answer why the change occurred: which inputs caused the change in metric? A key componen…
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
Jivat Neet Kaur, Emre Kiciman, Amit Sharma
Recent empirical studies on domain generalization (DG) have shown that DG algorithms that perform well on some distribution shifts fail on others, and no state-of-the-art DG algori…