Publications

ML Evaluation

  • Binette, O., & Reiter, J. P. (2024). Improving the Validity and Practical Usefulness of AI/ML Evaluations Using an Estimands Framework. arXiv e-prints, arXiv:2406.10366. [link]

  • Binette, O. and J. P. Reiter (2023) ER-Evaluation: End-to-End Evaluation of Entity Resolution Systems. Journal of Open Source Software, 8(91), 5619. [link]

  • Binette, O., S. A. York, E. Hickerson, Y. Baek, S. Madhavan and C. Jones. (2023) Estimating the Performance of Entity Resolution Algorithms: Lessons Learned Through PatentsView.org. The American Statistician [link]

  • Binette, O., S. Madhavan, J. Butler, B.A. Card, E. Melluso and C. Jones. (2023) PatentsView-Evaluation: Evaluation Datasets and Tools to Advance Research on Inventor Name Disambiguation. arXiv e-prints, arxiv:2301.03591 [link]

  • Binette, O. and R.C. Steorts (2021) On the Reliability of Multiple Systems Estimation for the Quantification of Modern Slavery. Journal of the Royal Statistical Society, Series A [link]

Entity Resolution

  • Bai, E., O. Binette and J. P. Reiter (2023) Optimal F-score Clustering for Bipartite Record Linkage. arxiv-eprints. arxiv:2311.13923 [link]

  • Binette, O. and R. C. Steorts (2021) (Almost) All of Entity Resolution. Science Advances 8 (12) [link]

Bayesian Nonparametrics

  • Binette, O., D. Pati, and D. B. Dunson (2020) Bayesian Closed Surface Fitting Through Tensor Products. Journal of Machine Learning Research 21 (119) pp. 1-26 [link]

  • Binette, O. (2019). A Note on Reverse Pinsker Inequalities. IEEE Transactions on Information Theory 65 (7). pp.4094-4096. [link]

  • Binette, O. and S. Guillotte (2019). Bayesian Nonparametrics for Directional Statistics. arXiv e-prints. arxiv:1807.00305. [link]