Machine Learning Model Drift Detection Via Weak Data Slices
- Samuel Ackerman
- Parijat Dube
- et al.
- 2021
- ICSE 2021
Publications
This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.
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14 results for Eitan Farchi
Detecting model drift using polynomial relations
- Eliran Roffe
- Samuel Ackerman
- et al.
- 2022
- AAAI 2022
Learner-Independent Targeted Data Omission Attacks
- Guy Barash
- Onn Shehory
- et al.
- 2020
- AAAI 2020
Generalized Coverage Criteria for Combinatorial Sequence Testing
- Achiya Elyasaf
- Eitan Farchi
- et al.
- 2024
- ICSE 2024
Density-based interpretable hypercube region partitioning for mixed numeric and categorical data
- Samuel Ackerman
- Eitan Farchi
- et al.
- 2021
- JSM 2021
Detection of data 'drift' over time affecting ML model performance
- Samuel Ackerman
- Orna Raz
- et al.
- 2019
- ISA Annual Meeting 2019
A Chaos Recommendation Tool for Reliability Testing in Large-Scale Cloud-Native Systems
- Mudit Verma
- Sandeep Hans
- et al.
- 2024
- COMSNET 2024
A Novel Double T-wise Approach to Root Cause Analysis via Combinatorial Test Set Completion
- Andrew Hicks
- Debbie Furman
- et al.
- 2024
- ICST 2024
Predicting Question-Answering Performance of Large Language Models through Semantic Consistency
- Ella Rabinovich
- Samuel Ackerman
- et al.
- 2023
- EMNLP 2023
Measuring the Measuring Tools: An Automatic Evaluation of Semantic Metrics for Text Corpora
- 2022
- EMNLP 2022