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Carlos Riquelme
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2020 – today
- 2024
- [j3]Tianlin Liu, Mathieu Blondel, Carlos Riquelme Ruiz, Joan Puigcerver:
Routers in Vision Mixture of Experts: An Empirical Study. Trans. Mach. Learn. Res. 2024 (2024) - [c19]Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut:
On Scaling Up a Multilingual Vision and Language Model. CVPR 2024: 14432-14444 - [c18]Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci:
Scaling Laws for Sparsely-Connected Foundation Models. ICLR 2024 - [c17]Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Neil Houlsby:
From Sparse to Soft Mixtures of Experts. ICLR 2024 - [i27]Tianlin Liu, Mathieu Blondel, Carlos Riquelme, Joan Puigcerver:
Routers in Vision Mixture of Experts: An Empirical Study. CoRR abs/2401.15969 (2024) - [i26]Marco Bellagente, Jonathan Tow, Dakota Mahan, Duy Phung, Maksym Zhuravinskyi, Reshinth Adithyan, James Baicoianu, Ben Brooks, Nathan Cooper, Ashish Datta, Meng Lee, Emad Mostaque, Michael Pieler, Nikhil Pinnaparaju, Paulo Rocha, Harry Saini, Hannah Teufel, Niccoló Zanichelli, Carlos Riquelme:
Stable LM 2 1.6B Technical Report. CoRR abs/2402.17834 (2024) - [i25]Nikhil Pinnaparaju, Reshinth Adithyan, Duy Phung, Jonathan Tow, James Baicoianu, Ashish Datta, Maksym Zhuravinskyi, Dakota Mahan, Marco Bellagente, Carlos Riquelme, Nathan Cooper:
Stable Code Technical Report. CoRR abs/2404.01226 (2024) - 2023
- [c16]Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, Neil Houlsby:
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints. ICLR 2023 - [c15]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. ICML 2023: 7480-7512 - [i24]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang
, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. CoRR abs/2302.05442 (2023) - [i23]Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut:
PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR abs/2305.18565 (2023) - [i22]Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Neil Houlsby:
From Sparse to Soft Mixtures of Experts. CoRR abs/2308.00951 (2023) - [i21]Elias Frantar, Carlos Riquelme, Neil Houlsby, Dan Alistarh, Utku Evci:
Scaling Laws for Sparsely-Connected Foundation Models. CoRR abs/2309.08520 (2023) - 2022
- [j2]James Urquhart Allingham, Florian Wenzel, Zelda E. Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin
Sparse MoEs meet Efficient Ensembles. Trans. Mach. Learn. Res. 2022 (2022) - [c14]Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic:
Which Model to Transfer? Finding the Needle in the Growing Haystack. CVPR 2022: 9195-9204 - [c13]Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby:
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. NeurIPS 2022 - [c12]Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli:
On the Adversarial Robustness of Mixture of Experts. NeurIPS 2022 - [i20]Cédric Renggli, André Susano Pinto, Neil Houlsby, Basil Mustafa, Joan Puigcerver, Carlos Riquelme:
Learning to Merge Tokens in Vision Transformers. CoRR abs/2202.12015 (2022) - [i19]Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby:
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. CoRR abs/2206.02770 (2022) - [i18]Xi Chen, Xiao Wang
PaLI: A Jointly-Scaled Multilingual Language-Image Model. CoRR abs/2209.06794 (2022) - [i17]Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli:
On the Adversarial Robustness of Mixture of Experts. CoRR abs/2210.10253 (2022) - [i16]Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, Neil Houlsby:
Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints. CoRR abs/2212.05055 (2022) - 2021
- [c11]Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Cédric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby:
Scalable Transfer Learning with Expert Models. ICLR 2021 - [c10]Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby:
Scaling Vision with Sparse Mixture of Experts. NeurIPS 2021: 8583-8595 - [i15]Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby:
Scaling Vision with Sparse Mixture of Experts. CoRR abs/2106.05974 (2021) - [i14]James Urquhart Allingham, Florian Wenzel, Zelda E. Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton:
Sparse MoEs meet Efficient Ensembles. CoRR abs/2110.03360 (2021) - 2020
- [c9]Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly:
Google Research Football: A Novel Reinforcement Learning Environment. AAAI 2020: 4501-4510 - [i13]Nicolas Brosse, Carlos Riquelme, Alice Martin, Sylvain Gelly, Eric Moulines:
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation. CoRR abs/2001.08049 (2020) - [i12]Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Cédric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby:
Scalable Transfer Learning with Expert Models. CoRR abs/2009.13239 (2020) - [i11]Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic:
Which Model to Transfer? Finding the Needle in the Growing Haystack. CoRR abs/2010.06402 (2020) - [i10]Basil Mustafa, Carlos Riquelme, Joan Puigcerver, André Susano Pinto, Daniel Keysers, Neil Houlsby:
Deep Ensembles for Low-Data Transfer Learning. CoRR abs/2010.06866 (2020)
2010 – 2019
- 2019
- [c8]Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin:
Practical and Consistent Estimation of f-Divergences. NeurIPS 2019: 4072-4082 - [c7]Carlos Riquelme, Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto, Gergely Neu:
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. NeurIPS 2019: 11872-11882 - [i9]Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin:
Practical and Consistent Estimation of f-Divergences. CoRR abs/1905.11112 (2019) - [i8]Hugo Penedones, Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy A. Mann, André Barreto, Sylvain Gelly, Gergely Neu:
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. CoRR abs/1906.07987 (2019) - [i7]Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly:
Google Research Football: A Novel Reinforcement Learning Environment. CoRR abs/1907.11180 (2019) - [i6]Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann
The Visual Task Adaptation Benchmark. CoRR abs/1910.04867 (2019) - 2018
- [c6]Sven Schmit, Carlos Riquelme:
Human Interaction with Recommendation Systems. AISTATS 2018: 862-870 - [c5]Carlos Riquelme, George Tucker, Jasper Snoek:
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. ICLR (Poster) 2018 - [i5]Carlos Riquelme, George Tucker, Jasper Snoek:
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling. CoRR abs/1802.09127 (2018) - 2017
- [c4]Carlos Riquelme, Ramesh Johari, Baosen Zhang:
Online Active Linear Regression via Thresholding. AAAI 2017: 2506-2512 - [c3]Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric:
Active Learning for Accurate Estimation of Linear Models. ICML 2017: 2931-2939 - [i4]Sven Schmit, Carlos Riquelme:
Human Interaction with Recommendation Systems: On Bias and Exploration. CoRR abs/1703.00535 (2017) - [i3]Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric:
Active Learning for Accurate Estimation of Linear Models. CoRR abs/1703.00579 (2017) - 2016
- [j1]Siddhartha Banerjee, Ramesh Johari, Carlos Riquelme:
Dynamic pricing in ridesharing platforms. SIGecom Exch. 15(1): 65-70 (2016) - [i2]Carlos Riquelme, Ramesh Johari, Baosen Zhang:
Online Active Linear Regression via Thresholding. CoRR abs/1602.02845 (2016) - 2015
- [c2]Siddhartha Banerjee, Ramesh Johari, Carlos Riquelme:
Pricing in Ride-Sharing Platforms: A Queueing-Theoretic Approach. EC 2015: 639 - 2014
- [c1]Austin R. Benson
Learning multifractal structure in large networks. KDD 2014: 1326-1335 - [i1]Austin R. Benson, Carlos Riquelme, Sven Schmit:
Learning multifractal structure in large networks. CoRR abs/1402.6787 (2014)
Coauthor Index
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