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07/28/2023
Adversarial training for tabular data with attack propagation
Adversarial attacks are a major concern in security-centered application...
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07/25/2023
The GANfather: Controllable generation of malicious activity to improve defence systems
Machine learning methods to aid defence systems in detecting malicious a...
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07/17/2023
From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs
Many real-world datasets have an underlying dynamic graph structure, whe...
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03/29/2023
Fairness-Aware Data Valuation for Supervised Learning
Data valuation is a ML field that studies the value of training instance...
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11/24/2022
Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation
Evaluating new techniques on realistic datasets plays a crucial role in ...
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10/25/2022
LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering
Anti-money laundering (AML) regulations mandate financial institutions t...
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09/16/2022
FairGBM: Gradient Boosting with Fairness Constraints
Machine Learning (ML) algorithms based on gradient boosted decision tree...
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07/18/2022
Lightweight Automated Feature Monitoring for Data Streams
Monitoring the behavior of automated real-time stream processing systems...
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07/13/2022
Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions
In recent years, machine learning algorithms have become ubiquitous in a...
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06/27/2022
Human-AI Collaboration in Decision-Making: Beyond Learning to Defer
Human-AI collaboration (HAIC) in decision-making aims to create synergis...
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06/27/2022
Prisoners of Their Own Devices: How Models Induce Data Bias in Performative Prediction
The unparalleled ability of machine learning algorithms to learn pattern...
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06/24/2022
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods
Machine Learning (ML) models now inform a wide range of human decisions,...
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05/07/2022
ConceptDistil: Model-Agnostic Distillation of Concept Explanations
Concept-based explanations aims to fill the model interpretability gap f...
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04/29/2022
Data+Shift: Supporting visual investigation of data distribution shifts by data scientists
Machine learning on data streams is increasingly more present in multipl...
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12/14/2021
Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs
Money laundering is a global problem that concerns legitimizing proceeds...
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07/16/2021
Active learning for online training in imbalanced data streams under cold start
Labeled data is essential in modern systems that rely on Machine Learnin...
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06/23/2021
Railgun: managing large streaming windows under MAD requirements
Some mission critical systems, e.g., fraud detection, require accurate, ...
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04/26/2021
Weakly Supervised Multi-task Learning for Concept-based Explainability
In ML-aided decision-making tasks, such as fraud detection or medical di...
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03/23/2021
Promoting Fairness through Hyperparameter Optimization
Considerable research effort has been guided towards algorithmic fairnes...
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02/10/2021
GuiltyWalker: Distance to illicit nodes in the Bitcoin network
Money laundering is a global phenomenon with wide-reaching social and ec...
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01/21/2021
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations
There have been several research works proposing new Explainable AI (XAI...
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11/30/2020
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations
Recurrent neural networks are a standard building block in numerous mach...
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11/27/2020
Teaching the Machine to Explain Itself using Domain Knowledge
Machine Learning (ML) has been increasingly used to aid humans to make b...
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10/07/2020
A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization
Considerable research effort has been guided towards algorithmic fairnes...
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09/24/2020
BreachRadar: Automatic Detection of Points-of-Compromise
Bank transaction fraud results in over 13B annual losses for banks, merc...
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09/01/2020
Railgun: streaming windows for mission critical systems
Some mission critical systems, such as fraud detection, require accurate...
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05/29/2020
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity
Every year, criminals launder billions of dollars acquired from serious ...
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02/14/2020
ARMS: Automated rules management system for fraud detection
Fraud detection is essential in financial services, with the potential o...
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02/14/2020
Interleaved Sequence RNNs for Fraud Detection
Payment card fraud causes multibillion dollar losses for banks and merch...
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08/12/2019
