Nave Frost

According to our database1, Nave Frost authored at least 26 papers between 2016 and 2024.

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Bibliography

2024
Optimizing Counterfactual-based Analysis of Machine Learning Models Through Databases.
Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024

Predicting Fact Contributions from Query Logs with Machine Learning.
Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024

2023
Banzhaf Values for Facts in Query Answering.
CoRR, 2023

2022
Toward Explainable Data Science
PhD thesis, 2022

Computing the Shapley Value of Facts in Query Answering.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

ShapGraph: An Holistic View of Explanations through Provenance Graphs and Shapley Values.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Framework for Evaluating Faithfulness of Local Explanations.
Proceedings of the International Conference on Machine Learning, 2022

LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
SmartTriage: A system for personalized patient data capture, documentation generation, and decision support.
Proceedings of the Machine Learning for Health, 2021

Explanations for Data Repair Through Shapley Values.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Explaining Natural Language query results.
VLDB J., 2020

Personal Insights for Altering Decisions of Tree-based Ensembles over Time.
Proc. VLDB Endow., 2020

SmartTriage: A system for personalized patient data capture, documentation generation, and decision support.
CoRR, 2020

ExKMC: Expanding Explainable k-Means Clustering.
CoRR, 2020

T-REx: Table Repair Explanations.
Proceedings of the 2020 International Conference on Management of Data, 2020

Explainable k-Means and k-Medians Clustering.
Proceedings of the 37th International Conference on Machine Learning, 2020

Explaining Missing Query Results in Natural Language.
Proceedings of the 23rd International Conference on Extending Database Technology, 2020

2019
Explaining Results of Data-Driven Applications.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Constraints-Based Explanations of Classifications.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Just in Time: Personal Temporal Insights for Altering Model Decisions.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

2018
Natural Language Explanations for Query Results.
SIGMOD Rec., 2018

NLProveNAns: Natural Language Provenance for Non-Answers.
Proc. VLDB Endow., 2018

Provenance for Non-Experts.
IEEE Data Eng. Bull., 2018

CEC: Constraints based Explanation for Classifications.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Provenance for Natural Language Queries.
Proc. VLDB Endow., 2017

2016
NLProv: Natural Language Provenance.
Proc. VLDB Endow., 2016


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