InfoMoD: Information-theoretic Model Diagnostics

Author:

Esmaeilzadeh Armin1ORCID,Golab Lukasz2ORCID,Taghva Kazem1ORCID

Affiliation:

1. UNLV, USA

2. University of Waterloo, Canada

Funder

NSERC

Publisher

ACM

Reference6 articles.

1. [ 1 ] A. Asudeh : Assessing and Remedying Coverage for a Given Dataset . ICDE 2019: 554-565 [1] A. Asudeh et al: Assessing and Remedying Coverage for a Given Dataset. ICDE 2019: 554-565

2. [ 2 ] Y. Chung A Big Data - AI Integration Approach. TKDE 32 ( 12 ): 2284 - 2296 ( 2020 ) [2] Y. Chung et al: Automated Data Slicing for Model Validation: A Big Data - AI Integration Approach. TKDE 32(12): 2284-2296 (2020)

3. [ 3 ] K. El Gebaly : Explanation Tables. IEEE Data Eng. Bull. 41 ( 3 ): 43 - 51 ( 2018 ) [3] K. El Gebaly et al: Explanation Tables. IEEE Data Eng. Bull. 41(3): 43-51 (2018)

4. [ 4 ] G. Feng : Scalable Informative Rule Mining . ICDE 2017: 437-448 [4] G. Feng et al: Scalable Informative Rule Mining. ICDE 2017: 437-448

5. [ 5 ] C. Molnar : Interpretable Machine Learning: A Guide for Making Black Box Models Explainable ( 2 nd ed.). 2022 [5] C. Molnar: Interpretable Machine Learning: A Guide for Making Black Box Models Explainable (2nd ed.). 2022

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1. AI ethics in a controversial industry: the case of gambling and its ethical paradox;AI and Ethics;2024-07-09

2. CAMO: Explaining Consensus Across MOdels;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

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