Machine learning algorithms generate predictions, recommendations and new content by analyzing and identifying patterns in their training data. These capabilities power widely used technologies such ...

Association rules are if-then statements that show the probability of relationships between data items within large data sets in various types of databases. At a basic level, association rule mining ...

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare program, which could be mitigated using lessons from machine learning. MA ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...