Carlos Riquelme

According to our database, Carlos Riquelme authored at least 30 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Stable LM 2 1.6B Technical Report.

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 Pinnaparju, Paulo Rocha, Harry Saini, Hannah Teufel, Niccoló Zanichelli, Carlos Riquelme

CoRR, 2024

Routers in Vision Mixture of Experts: An Empirical Study.

Tianlin Liu, Mathieu Blondel, Carlos Riquelme, Joan Puigcerver

CoRR, 2024

2023

Scaling Laws for Sparsely-Connected Foundation Models.

Elias Frantar, Carlos Riquelme, Neil Houlsby, Dan Alistarh, Utku Evci

CoRR, 2023

From Sparse to Soft Mixtures of Experts.

Joan Puigcerver, Carlos Riquelme, Basil Mustafa, Neil Houlsby

CoRR, 2023

PaLI-X: On Scaling up a Multilingual Vision and Language Model.

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

CoRR, 2023

Scaling Vision Transformers to 22 Billion Parameters.

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 N. Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby

CoRR, 2023

Scaling Vision Transformers to 22 Billion Parameters.

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

Proceedings of the International Conference on Machine Learning, 2023

Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints.

Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, Neil Houlsby

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Sparse MoEs meet Efficient Ensembles.

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

Trans. Mach. Learn. Res., 2022

PaLI: A Jointly-Scaled Multilingual Language-Image Model.

Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut

CoRR, 2022

Learning to Merge Tokens in Vision Transformers.

Cédric Renggli, André Susano Pinto, Neil Houlsby, Basil Mustafa, Joan Puigcerver, Carlos Riquelme

CoRR, 2022

On the Adversarial Robustness of Mixture of Experts.

Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts.

Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Which Model to Transfer? Finding the Needle in the Growing Haystack.

Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Scaling Vision with Sparse Mixture of Experts.

Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalable Transfer Learning with Expert Models.

Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Cédric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Deep Ensembles for Low-Data Transfer Learning.

Basil Mustafa, Carlos Riquelme, Joan Puigcerver, André Susano Pinto, Daniel Keysers, Neil Houlsby

CoRR, 2020

On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation.

Nicolas Brosse, Carlos Riquelme, Alice Martin, Sylvain Gelly, Eric Moulines

CoRR, 2020

Google Research Football: A Novel Reinforcement Learning Environment.

Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

The Visual Task Adaptation Benchmark.

Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby

CoRR, 2019

Practical and Consistent Estimation of f-Divergences.

Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates.

Carlos Riquelme, Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto, Gergely Neu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling.

Carlos Riquelme, George Tucker, Jasper Snoek

Proceedings of the 6th International Conference on Learning Representations, 2018

Human Interaction with Recommendation Systems.

Sven Schmit, Carlos Riquelme

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Human Interaction with Recommendation Systems: On Bias and Exploration.

Sven Schmit, Carlos Riquelme

CoRR, 2017

Active Learning for Accurate Estimation of Linear Models.

Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric

Proceedings of the 34th International Conference on Machine Learning, 2017

Online Active Linear Regression via Thresholding.

Carlos Riquelme, Ramesh Johari, Baosen Zhang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Dynamic pricing in ridesharing platforms.

Siddhartha Banerjee, Ramesh Johari, Carlos Riquelme

SIGecom Exch., 2016

2015

Pricing in Ride-Sharing Platforms: A Queueing-Theoretic Approach.

Siddhartha Banerjee, Ramesh Johari, Carlos Riquelme

Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

2014

Learning multifractal structure in large networks.

Austin R. Benson, Carlos Riquelme, Sven Schmit

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014