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Found 9 papers, 2 papers with code
Comparative Evaluation of Anomaly Detection Methods for Fraud Detection in Online Credit Card Payments
This observation challenges the potential benefits of ensemble methods to combine supervised, and AD approaches to enhance performance.
Benchmarking Robustness of Deep Reinforcement Learning approaches to Online Portfolio Management
Deep Reinforcement Learning approaches to Online Portfolio Selection have grown in popularity in recent years.
Evaluating resampling methods on a real-life highly imbalanced online credit card payments dataset
Various problems of any credit card fraud detection based on machine learning come from the imbalanced aspect of transaction datasets.
TracInAD: Measuring Influence for Anomaly Detection
As with many other tasks, neural networks prove very effective for anomaly detection purposes.
Bayesian and Dempster-Shafer models for combining multiple sources of evidence in a fraud detection system
Combining evidence from different sources can be achieved with Bayesian or Dempster-Shafer methods.
Financial Time Series Data Processing for Machine Learning
This article studies the financial time series data processing for machine learning.
Seq2Seq and Multi-Task Learning for joint intent and content extraction for domain specific interpreters
This study evaluates the performances of an LSTM network for detecting and extracting the intent and content of com- mands for a financial chatbot.
Stock Chart Pattern recognition with Deep Learning
This study evaluates the performances of CNN and LSTM for recognizing common charts patterns in a stock historical data.
Using NLP on news headlines to predict index trends
This paper attempts to provide a state of the art in trend prediction using news headlines.
