Summary

I propose to develop improved Machine Learning techniques for working with large-scale ordinal datasets, including applications to embedding and similarity search for Natural Language Processing and Information Retrieval.

Committee Members

Advisor's Comments on Committee

Javed Aslam is Jesse's advisor. David Smith has expertise in natural language processing, information retrieval, and machine learning, all of which are relevant to Jesse's dissertation work. Byron Wallace has expertise in machine learning and a specific interest in embeddings, all relevant to Jesse's dissertation work. Fernando Diaz (external committee member) has expertise in information retrieval and an interest in the application of embedding techniques to music recommendation—the subject of Jesse's recent internship and a thesis topic.

Proposal

Additional Manuscripts

  • Measuring Human-perceived Similarity in Heterogeneous Collections (pdf; unpublished manuscript, 2014)
  • Triple Selection for Ordinal Embedding (pdf; unpublished manuscript, 2016)
  • Revealing the Basis: Ordinal Embedding Through Geometry (pdf; unpublished manuscript, 2016)