Dan Shiebler

Publication Activity (10 Years)

Years Active: 2018-2022
Publications (10 Years): 15

Top Topics

Recommendation Systems

Machine Learning

Stochastic Processes

Overlapping Clustering

Top Venues

Compositionality

Publications

Dan Shiebler
Kan Extensions in Data Science and Machine Learning. CoRR (2022)
Dan Shiebler
Flattening Multiparameter Hierarchical Clustering Functors. CoRR (2021)
Dan Shiebler
Generalized Optimization: A First Step Towards Category Theoretic Learning Theory. ICO (2021)
Alim Virani, Jay Baxter, Dan Shiebler, Philip Gautier, Shivam Verma, Yan Xia, Apoorv Sharma, Sumit Binnani, Linlin Chen, Chenguang Yu
Lessons Learned Addressing Dataset Bias in Model-Based Candidate Generation at Twitter. CoRR (2021)
Dan Shiebler
Categorical Stochastic Processes and Likelihood. Compositionality 3 (2021)
Dan Shiebler, Bruno Gavranovic, Paul W. Wilson
Category Theory in Machine Learning. CoRR (2021)
Dan Shiebler
Generalized Optimization: A First Step Towards Category Theoretic Learning Theory. CoRR (2021)
Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein
Tuning Word2vec for Large Scale Recommendation Systems. CoRR (2020)
Dan Shiebler
Categorical Stochastic Processes and Likelihood. CoRR (2020)
Dan Shiebler
Functorial Manifold Learning and Overlapping Clustering. CoRR (2020)
Dan Shiebler, Alexis Toumi, Mehrnoosh Sadrzadeh
Incremental Monoidal Grammars. CoRR (2020)
Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein
Tuning Word2vec for Large Scale Recommendation Systems. RecSys (2020)
Drew Linsley, Dan Shiebler, Sven Eberhardt, Thomas Serre
Learning what and where to attend. ICLR (Poster) (2019)
Dan Shiebler, Luca Belli, Jay Baxter, Hanchen Xiong, Abhishek Tayal
Fighting Redundancy and Model Decay with Embeddings. CoRR (2018)
Dan Shiebler
A Correlation Maximization Approach for Cross Domain Co-Embeddings. CoRR (2018)