Samuel Ackerman

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 23

Top Topics

Categorical Data

Drift Detection

Top Venues

Publications

Samuel Ackerman, Eitan Farchi, Rami Katan, Orna Raz
Using Combinatorial Optimization to Design a High quality LLM Solution. CoRR (2024)
Samuel Ackerman, Axel Bendavid, Eitan Farchi, Orna Raz
Automatic Generation of Attention Rules For Containment of Machine Learning Model Errors. CoRR (2023)
Dipak Wani, Samuel Ackerman, Eitan Farchi, Xiaotong Liu, Hau-wen Chang, Sarasi Lalithsena
Data Drift Monitoring for Log Anomaly Detection Pipelines. CoRR (2023)
Ella Rabinovich, Matan Vetzler, Samuel Ackerman, Ateret Anaby-Tavor
Reliable and Interpretable Drift Detection in Streams of Short Texts. ACL (industry) (2023)
Ella Rabinovich, Matan Vetzler, Samuel Ackerman, Ateret Anaby-Tavor
Reliable and Interpretable Drift Detection in Streams of Short Texts. CoRR (2023)
Samuel Ackerman, George Kour, Eitan Farchi
Characterizing how 'distributional' NLP corpora distance metrics are. CoRR (2023)
Samuel Ackerman, Lincoln Alexander, Margaret Bennett, Donglin Chen, Eitan Farchi, Autumn Houseknecht, Padmanabhan Santhanam
Deploying automated ticket router across the enterprise. AI Mag. 44 (1) (2023)
Ella Rabinovich, Samuel Ackerman, Orna Raz, Eitan Farchi, Ateret Anaby-Tavor
Predicting Question-Answering Performance of Large Language Models through Semantic Consistency. CoRR (2023)
George Kour, Samuel Ackerman, Orna Raz, Eitan Farchi, Boaz Carmeli, Ateret Anaby-Tavor
Measuring the Measuring Tools: An Automatic Evaluation of Semantic Metrics for Text Corpora. CoRR (2022)
Samuel Ackerman, Ateret Anaby-Tavor, Eitan Farchi, Esther Goldbraich, George Kour, Ella Rabinovich, Orna Raz, Saritha Route, Marcel Zalmanovici, Naama Zwerdling
High-quality Conversational Systems. CoRR (2022)
Samuel Ackerman, Eitan Farchi, Orna Raz, Onn Shehory
Experiment Based Crafting and Analyzing of Machine Learning Solutions. CoRR (2022)
Samuel Ackerman, Eitan Farchi, Orna Raz, Marcel Zalmanovici, Maya Zohar
Density-based interpretable hypercube region partitioning for mixed numeric and categorical data. CoRR (2021)
Samuel Ackerman, Orna Raz, Marcel Zalmanovici
FreaAI: Automated extraction of data slices to test machine learning models. CoRR (2021)
Samuel Ackerman, Sanjib Choudhury, Nirmit Desai, Eitan Farchi, Dan Gisolfi, Andrew Hicks, Saritha Route, Diptikalyan Saha
Towards API Testing Across Cloud and Edge. CoRR (2021)
Samuel Ackerman, Parijat Dube, Eitan Farchi, Orna Raz, Marcel Zalmanovici
Machine Learning Model Drift Detection Via Weak Data Slices. CoRR (2021)
Samuel Ackerman, Parijat Dube, Eitan Farchi, Orna Raz, Marcel Zalmanovici
Machine Learning Model Drift Detection Via Weak Data Slices. DeepTest@ICSE (2021)
George Kour, Marcel Zalmanovici, Orna Raz, Samuel Ackerman, Ateret Anaby-Tavor
Classifier Data Quality: A Geometric Complexity Based Method for Automated Baseline And Insights Generation. CoRR (2021)
Samuel Ackerman, Parijat Dube, Eitan Farchi
Using sequential drift detection to test the API economy. CoRR (2021)
Eliran Roffe, Samuel Ackerman, Orna Raz, Eitan Farchi
Detecting model drift using polynomial relations. CoRR (2021)
Samuel Ackerman, Orna Raz, Marcel Zalmanovici, Aviad Zlotnick
Automatically detecting data drift in machine learning classifiers. CoRR (2021)
Samuel Ackerman, Eitan Farchi, Orna Raz, Marcel Zalmanovici, Parijat Dube
Detection of data drift and outliers affecting machine learning model performance over time. CoRR (2020)
Samuel Ackerman, Parijat Dube, Eitan Farchi
Sequential Drift Detection in Deep Learning Classifiers. CoRR (2020)
Samuel Ackerman
Consistency of survey opinions and external data. Comput. Stat. 34 (4) (2019)