86 citations · 572 across the 39 of their papers we have counts for
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stat.ML2018★ 12 cited
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport
Adarsh Subbaswamy, Peter Schulam, Suchi Saria
Classical supervised learning produces unreliable models when training and target distributions differ, with most existing solutions requiring samples from the target domain. We pr…
stat.ML2018★ 2 cited
Discretizing Logged Interaction Data Biases Learning for Decision-Making
Peter Schulam, Suchi Saria
Time series data that are not measured at regular intervals are commonly discretized as a preprocessing step. For example, data about customer arrival times might be simplified by…
stat.ML2018★ 14 cited
Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms
Adarsh Subbaswamy, Suchi Saria
Predictive models can fail to generalize from training to deployment environments because of dataset shift, posing a threat to model reliability and the safety of downstream decisi…