Triplet Constrained Representation Learning is a method of organizing a corpus of text into latent semantic groups based on relavancy to a predetermined notion. This project is being lead through a creative inquiry at Clemson University, and the proper explantaion of this method is explained in full by the project lead, in this PDF
- Test our method on MNIST
- Create triplet function based on Stochastic Triplet Embedding [✔]
- Implement loss function based on triplet function in pytorch [ ]
- Simulate researcher feedback with metacriteria for triplet labels [✔]
- Compare our methods accuracy with others to determine usefulness [ ]
- Use refined method with textual dataset
- Group based on latent semantic findings in the text
- Researcher feedback loop with metacriteria to group uncertain groups
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- TBA