Mike Gartrell

Principal Researcher, Rhizome Labs

Joined

July 2019

Names

Mike Gartrell

Emails

****@criteo.com (Confirmed)

****@gmail.com (Confirmed)

****@sigmanova.ai (Confirmed)

****@rhizome-labs.com (Confirmed)

Personal Links

Career & Education History

Principal Researcher

Rhizome Labs (rhizome-labs.com)

2026 – Present

Principal Researcher

Sigma Nova (sigmanova.ai)

2024 – 2025

Senior Researcher

Criteo AI Lab (criteo.com)

2017 – 2023

Postdoc

Microsoft (microsoft.com)

2014 – 2016

PhD student

University of Colorado, Boulder (colorado.edu)

2008 – 2014

Advisors, Relations & Conflicts

Coauthor

Insu Han

2020 – Present

Coauthor and collaborator

Zelda Mariet

2017 – Present

Postdoc Advisor

Noam Koenigstein

2014 – 2016

PhD Advisor

Richard Han

2008 – 2014

Expertise

generative models

2022 – Present

embedding models

2016 – Present

unsupervised learning

2015 – Present

determinantal point processes

2014 – Present

recommender systems

2010 – 2021

Publications

Differentially Private Gradient Flow based on the Sliced Wasserstein Distance
Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi, Alain Rakotomamonjy, Mike Gartrell, Jamal Atif, Alexandre Allauzen
- Accepted by TMLR
- Readers: Everyone
Unifying GANs and Score-Based Diffusion as Generative Particle Models
Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bezenac, Mickael Chen, Alain Rakotomamonjy
- NeurIPS 2023 poster
- Readers: Everyone
Learning from Multiple Sources for Data-to-Text and Text-to-Data
Song Duong, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari
- 2023 (modified: 24 Apr 2023)
- CoRR 2023
- Readers: Everyone
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes
Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi
- Published: 01 Jan 2022, Last Modified: 05 May 2023
- ICML 2022
- Readers: Everyone
Scalable Sampling for Nonsymmetric Determinantal Point Processes
Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi
- Published: 01 Jan 2022, Last Modified: 05 May 2023
- ICLR 2022
- Readers: Everyone
Scalable Sampling for Nonsymmetric Determinantal Point Processes
Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, amin karbasi
- Published: 28 Jan 2022, Last Modified: 12 Oct 2025
- ICLR 2022 Spotlight
- Readers: Everyone
Bayesian Causal Inference for Real World Interactive Systems
Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang
- 2021 (modified: 13 Sept 2021)
- KDD 2021
- Readers: Everyone
Combining Reward and Rank Signals for Slate Recommendation
Imad Aouali, Sergey Ivanov, Mike Gartrell, David Rohde, Flavian Vasile, Victor Zaytsev, Diego Legrand
- Published: 01 Jan 2021, Last Modified: 05 May 2023
- CoRR 2021
- Readers: Everyone
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
- Published: 01 Jan 2021, Last Modified: 05 May 2023
- ICLR 2021
- Readers: Everyone
Wasserstein Learning of Determinantal Point Processes
Lucas Anquetil, Mike Gartrell, Alain Rakotomamonjy, Ugo Tanielian, Clément Calauzènes
- Published: 12 Dec 2020, Last Modified: 26 May 2025
- LMCA2020 Poster
- Readers: Everyone

View all 18 publications

Co-Authors

View all 43 co-authors