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Activity Number:
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559
- Foundations of Data Science: The TRIPODS Experience
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Type:
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Invited
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Date/Time:
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Thursday, August 6, 2020 : 3:00 PM to 4:50 PM
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Sponsor:
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Section on Statistical Learning and Data Science
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Abstract #309315
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Title:
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Riemannian Embedding Models for Relational Data
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Author(s):
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Abel Rodriguez*
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Companies:
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University of California, Santa Cruz
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Keywords:
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Factor Analysis;
Riemannian manyfolds;
Topological Data Analysis
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Abstract:
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We describe a novel class of factor models for categorical data. Rather than embedding multivariate discrete response onto a low dimensional Euclidean space, these models embed them into a more general (prespecified) low-dimensional manifold. This approach endows the model with greater expressive power without sacrificing interpretability. We will particularly focus on models for spherical embeddings, which are readily motivated by applications in political science.
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Authors who are presenting talks have a * after their name.
