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Found 6 papers, 2 papers with code
A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions
In lending, where prices are specific to both customers and products, having a well-functioning personalized pricing policy in place is essential to effective business making.
Sample-Level Weighting for Multi-Task Learning with Auxiliary Tasks
Multi-task learning (MTL) can improve the generalization performance of neural networks by sharing representations with related tasks.
HydaLearn: Highly Dynamic Task Weighting for Multi-task Learning with Auxiliary Tasks
Multi-task learning (MTL) can improve performance on a task by sharing representations with one or more related auxiliary-tasks.
The foundations of cost-sensitive causal classification
The framework is shown to instantiate to application-specific cost-sensitive performance measures that have been recently proposed for evaluating customer retention and response uplift models, and allows to maximize profitability when adopting a causal classification model for optimizing decision-making.
Autoencoders for strategic decision support
However, few data-driven tools that support strategic decision-making are available.
Optimising Individual-Treatment-Effect Using Bandits
Applying causal inference models in areas such as economics, healthcare and marketing receives great interest from the machine learning community.
