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"Feedzai Intelligence Network (FIN)" Podcast
6 Videos • Playlist
Animated Product Videos
5 Videos • Playlist
Anti-Money Laundering
8 Videos • Playlist
Latest
17:22
Active Learning for Imbalanced Data Under Cold Start – ICAIF’21
Modern systems that rely on Machine Learning (ML) for predictive modeling, may suffer from the cold-start problem: supervised models work […]
11:14
Human-AI Collaboration in Decision-Making: Beyond Learning to Defer
Authors: Diogo Leitão, Pedro Saleiro, Mário A. T. Figueiredo, Pedro Bizarro Human-AI collaboration (HAIC) in decision-making aims to create synergistic […]
04:57
Prisoners of Their Own Devices: How Models Induce Data Bias in Performative Prediction
The unparalleled ability of machine learning algorithms to learn patterns from data also enables them to incorporate biases embedded within. […]
08:30
Anti-Money Laundering Alert Optimization Using Machine Learning Graphs
Money laundering is a global problem that concerns legitimizing proceeds from serious felonies (1.7-4 trillion euros annually) such as drug […]
09:28
Understanding Unfairness in Fraud Detection Through Model and Data Bias Interactions
The unparalleled ability of machine learning algorithms to learn patterns from data also enables them to incorporate biases embedded within. […]
18:02
Data+Shift: Supporting Visual Investigation of Data Distribution Shifts by Data Scientists
Machine learning on data streams is increasingly present in multiple domains. However, there is often data distribution shift that can […]
22:38
FairGBM: Gradient Boosting with Fairness Constraints (Cutting Edge Machine Learning)
FairGBM is game-changing algorithm for Fair Machine Learning that is open source for non-commercial uses, making it accessible to everyone! […]
04:57
Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation (Fair ML)
Fair ML: What tabular dataset should be use when evaluating fair machine learning? Don’t miss this short webinar, and for […]
10:10
Fairness-Aware Data Valuation for Supervised Learning (Fair Machine Learning)
For more on fair machine learning, bias and fairness in coding, and AI in risk management, please subscribe to our […]
23:19
Interviewing Screen Reader Users to Build Accessible Charts
In this talk, Diogo and Rita share the main insights gathered during a series of interviews with screen reader users […]
16:18
How to Design Accessible Charts for the Web
In this talk, Rita discusses possible approaches to create accessible visualizations for the web. Specifically, how to handle images and […]
11:06
Graph-Sprints: A Low-Latency Node Embedding Framework on Continuous-Time Dynamic Graphs
Abstract: Many real-world datasets have an underlying dynamic graph structure, where entities and their interactions evolve over time. Machine learning […]
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