| Dynamic Pricing in Ridesharing Platforms S Banerjee, R Johari, C Riquelme ACM SIGecom Exchanges 15 (1), 65-70, 2016 | 93* | 2016 |
| Pricing in ride-sharing platforms: A queueing-theoretic approach S Banerjee, R Johari, C Riquelme Proceedings of the Sixteenth ACM Conference on Economics and Computation …, 2015 | 90 | 2015 |
| Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C Riquelme, G Tucker, J Snoek Sixth International Conference on Learning Representations, ICLR 2018., 2018 | 64 | 2018 |
| Pricing in ride-share platforms: A queueing-theoretic approach C Riquelme, S Banerjee, R Johari Available at SSRN, 2015 | 26 | 2015 |
| Online Active Linear Regression via Thresholding C Riquelme, R Johari, B Zhang AAAI-17, Thirty-First AAAI Conference on Artificial Intelligence., 2017 | 15 | 2017 |
| Human Interaction with Recommendation Systems S Schmit, C Riquelme The 21st International Conference on Artificial Intelligence and Statistics …, 2018 | 14 | 2018 |
| Learning Multifractal Structure in Large Networks AR Benson, C Riquelme, S Schmit Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 10 | 2014 |
| The visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 8 | 2019 |
| The Beta-VAE's Implicit Prior MD Hoffman, C Riquelme, M Johnson Bayesian Deep Learning Workshop. Neural Information Processing Systems, NIPS …, 2017 | 6 | 2017 |
| Pricing in ride-share platforms: A queueing-theoretic approach.(2015) S Banerjee, C Riquelme, R Johari Available at SSRN 2568258, 2015 | 6 | 2015 |
| Google research football: A novel reinforcement learning environment K Kurach, A Raichuk, P Stańczyk, M Zając, O Bachem, L Espeholt, ... arXiv preprint arXiv:1907.11180, 2019 | 5 | 2019 |
| Active Learning for Accurate Estimation of Linear Models C Riquelme, M Ghavamzadeh, A Lazaric Thirty-fourth International Conference on Machine Learning, ICML 2017., 2017 | 5 | 2017 |
| Practical and Consistent Estimation of f-Divergences P Rubenstein, O Bousquet, J Djolonga, C Riquelme, IO Tolstikhin Advances in Neural Information Processing Systems, 4072-4082, 2019 | 4 | 2019 |
| Human interaction with recommendation systems: On bias and exploration S Schmit, C Riquelme stat 1050, 1, 2017 | 2 | 2017 |
| Failure modes of variational inference for decision making C Riquelme, M Johnson, M Hoffman Prediction and Generative Modeling in RL Workshop (AAMAS, ICML, IJCAI), 2018 | 1 | 2018 |
| On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation N Brosse, C Riquelme, A Martin, S Gelly, É Moulines arXiv preprint arXiv:2001.08049, 2020 | | 2020 |
| Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates H Penedones, C Riquelme, D Vincent, H Maennel, T Mann, A Barreto, ... arXiv preprint arXiv:1906.07987, 2019 | | 2019 |
| Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates C Riquelme, H Penedones, D Vincent, H Maennel, S Gelly, TA Mann, ... Advances in Neural Information Processing Systems, 11872-11882, 2019 | | 2019 |
| Google Research Football: A Novel Reinforcement Learning Environment A Raichuk, C Riquelme, D Vincent, K Kurach, L Espeholt, M Michalski, ... | | 2019 |
| Knowledge Discovery from Belief Networks C Riquelme, E Koh US Patent US 9691032 B2, 2017 | | 2017 |
Siddhartha BanerjeeAssistant Professor, Operations Research, Cornell UniversityVerified email at cornell.edu
