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03/17/2022
Kan Extensions in Data Science and Machine Learning
A common problem in data science is "use this function defined over this...
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09/20/2021
Generalized Optimization: A First Step Towards Category Theoretic Learning Theory
The Cartesian reverse derivative is a categorical generalization of reve...
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06/13/2021
Category Theory in Machine Learning
Over the past two decades machine learning has permeated almost every re...
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05/13/2021
Lessons Learned Addressing Dataset Bias in Model-Based Candidate Generation at Twitter
Traditionally, heuristic methods are used to generate candidates for lar...
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04/30/2021
Flattening Multiparameter Hierarchical Clustering Functors
We bring together topological data analysis, applied category theory, an...
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11/15/2020
Functorial Manifold Learning and Overlapping Clustering
We adapt previous research on topological unsupervised learning to devel...
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09/24/2020
Tuning Word2vec for Large Scale Recommendation Systems
Word2vec is a powerful machine learning tool that emerged from Natural L...
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05/10/2020
Categorical Stochastic Processes and Likelihood
In this work we take a Category Theoretic perspective on the relationshi...
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01/02/2020
Incremental Monoidal Grammars
In this work we define formal grammars in terms of free monoidal categor...
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09/18/2018
Fighting Redundancy and Model Decay with Embeddings
Every day, hundreds of millions of new Tweets containing over 40 languag...
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09/10/2018