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20172026
most citedCounterfactual Shapley Additive Explanations

65 citations · 158 across the 27 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.LG2021

Tradeoffs in Streaming Binary Classification under Limited Inspection Resources

Parisa Hassanzadeh, Danial Dervovic, Samuel Assefa +2

Institutions are increasingly relying on machine learning models to identify and alert on abnormal events, such as fraud, cyber attacks and system failures. These alerts often need…

cs.LG2021★ 65 cited

Counterfactual Shapley Additive Explanations

Emanuele Albini, Jason Long, Danial Dervovic +1

Feature attributions are a common paradigm for model explanations due to their simplicity in assigning a single numeric score for each input feature to a model. In the actionable r…

cs.LG2021★ 10 cited

Counterfactual Explanations for Arbitrary Regression Models

Thomas Spooner, Danial Dervovic, Jason Long +3

We present a new method for counterfactual explanations (CFEs) based on Bayesian optimisation that applies to both classification and regression models. Our method is a globally co…

cs.AI2021★ 3 cited

Non-Parametric Stochastic Sequential Assignment With Random Arrival Times

Danial Dervovic, Parisa Hassanzadeh, Samuel Assefa +1

We consider a problem wherein jobs arrive at random times and assume random values. Upon each job arrival, the decision-maker must decide immediately whether or not to accept the j…

stat.ME2021

Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set

Yuanlu Bai, Tucker Balch, Haoxian Chen +3

Stochastic simulation aims to compute output performance for complex models that lack analytical tractability. To ensure accurate prediction, the model needs to be calibrated and v…