The project is about an algorithm, Information Sieves (IS), development based on work of Galstyan and Steeg (2016). The objective of this project is to assess this algorithm’s performance and find possible improvements or new applications. The data sets would be something larger than the small data sets used in Galstyan and Steeg’s work.
This midterm report was well organized and written, which showed the team members understood the IS method. The main concepts of the IS algorithm were also introduced. The project goal and plan are generally clear. The term “latent variable” was introduced.
There are something could be improved or be done in the future work.
- At least one data set need to be tested by using the IS algorithm. The data set can be the same or similar data set used in Galstyan and Steeg’s paper. The preliminary results can be compared with the results in their paper.
- Identify one or two target data sets. Address the midterm report goals, such as describing these data sets.
- The project would be more impressive if an example of the latent variable could be explained in the target data set.
The project is about an algorithm, Information Sieves (IS), development based on work of Galstyan and Steeg (2016). The objective of this project is to assess this algorithm’s performance and find possible improvements or new applications. The data sets would be something larger than the small data sets used in Galstyan and Steeg’s work.
This midterm report was well organized and written, which showed the team members understood the IS method. The main concepts of the IS algorithm were also introduced. The project goal and plan are generally clear. The term “latent variable” was introduced.
There are something could be improved or be done in the future work.