Publications
Feedzai Research publishes a series of in-depth articles and research papers on a regular basis. Most of these publications are culminations of fruitful collaboration with leading experts, men and women at world-class research institutions and universities. Our purpose is to keep the research community abreast of the latest in our journey of innovation.
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2024
Aequitas Flow: Streamlining Fair ML Experimentation
Published at Journal of Machine Learning Research
Show Me What’s Wrong!: Combining Charts and Text to Guide Data Analysis
Published at NLVIZ, a workshop at IEEE VIS 2024
Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints
Published at Transactions on Machine Learning Research (07/2024)
2023
Adversarial training for tabular data with attack propagation
Published at KDD Workshop on Machine Learning in Finance 2023
A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies
Published at ICLR 2023 workshop Trustworthy ML
Fairness-Aware Data Valuation for Supervised Learning
Published at ICLR 2023 workshop Trustworthy ML
2022
Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs
Published at AAAI - AI in Financial Services: Adaptiveness, Resilience & Governance workshop’2022
2021
2020
Interleaved Sequence RNNs for Fraud Detection
Published at KDD 2020 conference
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2019
2017
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