Summary of Consistent Joint Decision-making with Heterogeneous Learning Models, by Hossein Rajaby Faghihi and Parisa Kordjamshidi
Consistent Joint Decision-Making with Heterogeneous Learning Models
by Hossein Rajaby Faghihi, Parisa Kordjamshidi
First submitted to arxiv on: 6 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Machine Learning (cs.LG); Logic in Computer Science (cs.LO)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The novel decision-making framework presented in this paper combines predictions from diverse machine learning models while utilizing external knowledge to promote consistency among decisions. The framework, built upon Integer Linear Programming (ILP), maps model predictions into globally normalized and comparable values by incorporating information about prior probability, confidence, and expected accuracy. This approach is demonstrated to outperform conventional baselines on multiple datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a way for different machine learning models to make decisions together, using extra information to make sure the decisions are consistent. It works by taking the predictions from each model and turning them into something that can be compared and combined. The results show that this approach does better than usual methods on several datasets. |
Keywords
* Artificial intelligence * Machine learning * Probability
