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2020 – today
- 2023
[c19]Song Duong, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari:
Learning from Multiple Sources for Data-to-Text and Text-to-Data. AISTATS 2023: 3733-3753- [c18]Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy:
Unifying GANs and Score-Based Diffusion as Generative Particle Models. NeurIPS 2023 - [c17]Clarine Vongpaseut, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari:
Evaluating the Generalization Property of Prefix-based Methods for Data-to-text Generation. CORIA-TALN (2) 2023: 73-81 - [i18]Song Duong, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari:
Learning from Multiple Sources for Data-to-Text and Text-to-Data. CoRR abs/2302.11269 (2023) - [i17]Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy:
Unifying GANs and Score-Based Diffusion as Generative Particle Models. CoRR abs/2305.16150 (2023) - [i16]Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi, Alain Rakotomamonjy, Mike Gartrell, Jamal Atif, Alexandre Allauzen:
Differentially Private Gradient Flow based on the Sliced Wasserstein Distance for Non-Parametric Generative Modeling. CoRR abs/2312.08227 (2023) - 2022
- [c16]Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
Scalable Sampling for Nonsymmetric Determinantal Point Processes. ICLR 2022 - [c15]Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi:
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. ICML 2022: 8213-8229 - [i15]Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
Scalable Sampling for Nonsymmetric Determinantal Point Processes. CoRR abs/2201.08417 (2022) - [i14]Insu Han, Mike Gartrell, Elvis Dohmatob, Amin Karbasi:
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes. CoRR abs/2207.00486 (2022) - 2021
- [c14]Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. ICLR 2021 - [c13]Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang
:
Bayesian Causal Inference for Real World Interactive Systems. KDD 2021: 4114-4115 - [i13]Imad Aouali, Sergey Ivanov, Mike Gartrell, David Rohde, Flavian Vasile, Victor Zaytsev, Diego Legrand:
Combining Reward and Rank Signals for Slate Recommendation. CoRR abs/2107.12455 (2021) - 2020
- [i12]Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. CoRR abs/2006.09862 (2020) - [i11]Lucas Anquetil, Mike Gartrell, Alain Rakotomamonjy, Ugo Tanielian, Clément Calauzènes:
Wasserstein Learning of Determinantal Point Processes. CoRR abs/2011.09712 (2020)
2010 – 2019
- 2019
- [j6]Jason Shuo Zhang, Mike Gartrell, Richard Han, Qin Lv, Shivakant Mishra:
GEVR: An Event Venue Recommendation System for Groups of Mobile Users. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3(1): 34:1-34:25 (2019) - [c12]Zelda Mariet, Mike Gartrell, Suvrit Sra:
Learning Determinantal Point Processes by Corrective Negative Sampling. AISTATS 2019: 2251-2260 - [c11]Romain Warlop, Jérémie Mary, Mike Gartrell:
Tensorized Determinantal Point Processes for Recommendation. KDD 2019: 1605-1615 - [c10]Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene:
Learning Nonsymmetric Determinantal Point Processes. NeurIPS 2019: 6715-6725 - [i10]Jason Shuo Zhang, Mike Gartrell, Richard Han, Qin Lv, Shivakant Mishra:
GEVR: An Event Venue Recommendation System for Groups of Mobile Users. CoRR abs/1903.10512 (2019) - [i9]Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob, Syrine Krichene:
Learning Nonsymmetric Determinantal Point Processes. CoRR abs/1905.12962 (2019) - [i8]Syrine Krichene, Mike Gartrell, Clément Calauzènes:
Embedding models for recommendation under contextual constraints. CoRR abs/1907.01637 (2019) - 2018
- [i7]Zelda Mariet, Mike Gartrell, Suvrit Sra:
Learning Determinantal Point Processes by Sampling Inferred Negatives. CoRR abs/1802.05649 (2018) - [i6]Ugo Tanielian, Mike Gartrell, Flavian Vasile:
Adversarial Training of Word2Vec for Basket Completion. CoRR abs/1805.08720 (2018) - [i5]Romain Warlop, Jérémie Mary, Mike Gartrell:
Basket Completion with Multi-task Determinantal Point Processes. CoRR abs/1805.09916 (2018) - [i4]Mike Gartrell, Elvis Dohmatob:
Deep Determinantal Point Processes. CoRR abs/1811.07245 (2018) - 2017
- [j5]Shuo Zhang, Khaled Alanezi, Mike Gartrell, Richard Han, Qin Lv, Shivakant Mishra:
Understanding Group Event Scheduling via the OutWithFriendz Mobile Application. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1(4): 175:1-175:19 (2017) - [c9]Mike Gartrell, Ulrich Paquet, Noam Koenigstein:
Low-Rank Factorization of Determinantal Point Processes. AAAI 2017: 1912-1918 - [i3]Shuo Zhang, Khaled Alanezi, Mike Gartrell, Richard Han, Qin Lv, Shivakant Mishra:
Understanding Group Event Scheduling via the OutWithFriendz Mobile Application. CoRR abs/1710.02609 (2017) - 2016
- [j4]Peng Zhang, Hansu Gu, Mike Gartrell, Tun Lu, Dayi Yang, Xianghua Ding, Ning Gu:
Group-based Latent Dirichlet Allocation (Group-LDA): Effective audience detection for books in online social media. Knowl. Based Syst. 105: 134-146 (2016) - [c8]Mike Gartrell, Ulrich Paquet, Noam Koenigstein:
Bayesian Low-Rank Determinantal Point Processes. RecSys 2016: 349-356 - [i2]Mike Gartrell, Ulrich Paquet, Noam Koenigstein:
Low-Rank Factorization of Determinantal Point Processes for Recommendation. CoRR abs/1602.05436 (2016) - [i1]Mike Gartrell, Ulrich Paquet, Noam Koenigstein:
The Bayesian Low-Rank Determinantal Point Process Mixture Model. CoRR abs/1608.04245 (2016) - 2015
- [j3]Junho Ahn, James Williamson, Mike Gartrell, Richard Han, Qin Lv, Shivakant Mishra:
Supporting Healthy Grocery Shopping via Mobile Augmented Reality. ACM Trans. Multim. Comput. Commun. Appl. 12(1s): 16:1-16:24 (2015) - 2014
- [c7]Allison June-Barlow Chaney, Mike Gartrell, Jake M. Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet:
A large-scale exploration of group viewing patterns. TVX 2014: 31-38 - 2013
- [c6]Hansu Gu, Mike Gartrell, Liang Zhang, Qin Lv, Dirk Grunwald:
AnchorMF: towards effective event context identification. CIKM 2013: 629-638 - 2012
- [j2]Aaron Beach, Mike Gartrell, Richard Han:
q-Anon: practical anonymity for social networks. Int. J. Soc. Comput. Cyber Phys. Syst. 1(3): 223-241 (2012) - 2010
- [c5]Mike Gartrell, Xinyu Xing, Qin Lv, Aaron Beach, Richard Han, Shivakant Mishra, Karim Seada:
Enhancing group recommendation by incorporating social relationship interactions. GROUP 2010: 97-106 - [c4]Aaron Beach, Mike Gartrell, Richard Han:
Social-K: Real-time K-anonymity guarantees for social network applications. PerCom Workshops 2010: 600-606 - [c3]Aaron Beach, Mike Gartrell, Richard Han:
q-Anon: Rethinking Anonymity for Social Networks. SocialCom/PASSAT 2010: 185-192 - [c2]Aaron Beach, Mike Gartrell, Xinyu Xing, Richard Han, Qin Lv, Shivakant Mishra, Karim Seada:
Fusing mobile, sensor, and social data to fully enable context-aware computing. HotMobile 2010: 60-65
2000 – 2009
- 2009
- [c1]Aaron Beach, Mike Gartrell, Richard Han:
Solutions to Security and Privacy Issues in Mobile Social Networking. CSE (4) 2009: 1036-1042 - 2008
- [j1]Aaron Beach, Mike Gartrell, Sirisha Akkala, Jack Elston, John Kelley, Keisuke Nishimoto, Baishakhi Ray, Sergei Razgulin, Karthik Sundaresan, Bonnie Surendar, Michael Terada, Richard Han:
WhozThat? evolving an ecosystem for context-aware mobile social networks. IEEE Netw. 22(4): 50-55 (2008)
Coauthor Index
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