Olivier Bachem
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
32
Venues
8
Active years
2015–2025
Best venue rank
A*
Where they publish
Papers
32 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Diversity-Rewarded CFG Distillation. | Geoffrey Cideron, Andrea Agostinelli, Johan Ferret, Sertan Girgin, Romuald Elie, Olivier Bachem, Sarah Perrin, Alexandre Ram |
| 2025 | ICLR | BOND: Aligning LLMs with Best-of-N Distillation. | Pier Giuseppe Sessa, Robert Dadashi-Tazehozi, Lonard Hussenot, Johan Ferret, Nino Vieillard, Alexandre Ram, Bobak Shahriari, Sarah Perrin, Abram L. Friesen, Geoffrey Cideron, Sertan Girgin, Piotr Stanczyk, Andrea Michi, Danila Sinopalnikov, Sabela Ramos Garea, Amlie Hliou, Aliaksei Severyn, Matthew Hoffman, Nikola Momchev, Olivier Bachem |
| 2024 | EMNLP | Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning. | Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ram, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Lonard Hussenot, Olivier Bachem, Edouard Leurent |
| 2024 | ICLR | On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes. | Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, Piotr Stanczyk, Sabela Ramos Garea, Matthieu Geist, Olivier Bachem |
| 2024 | ICML | MusicRL: Aligning Music Generation to Human Preferences. | Geoffrey Cideron, Sertan Girgin, Mauro Verzetti, Damien Vincent, Matej Kastelic, Zaln Borsos, Brian McWilliams, Victor Ungureanu, Olivier Bachem, Olivier Pietquin, Matthieu Geist, Lonard Hussenot, Neil Zeghidour, Andrea Agostinelli |
| 2024 | ICML | Nash Learning from Human Feedback. | Rmi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Cme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot |
| 2024 | ICML | WARM: On the Benefits of Weight Averaged Reward Models. | Alexandre Ram, Nino Vieillard, Lonard Hussenot, Robert Dadashi, Geoffrey Cideron, Olivier Bachem, Johan Ferret |
| 2023 | ACL | Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. | Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Lonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos Garea, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor |
| 2022 | AAAI | Offline Reinforcement Learning as Anti-exploration. | Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Lonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist |
| 2022 | AISTATS | A general class of surrogate functions for stable and efficient reinforcement learning. | Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux |
| 2022 | EMNLP | Decoding a Neural Retriever's Latent Space for Query Suggestion. | Leonard Adolphs, Michelle Chen Huebscher, Christian Buck, Sertan Girgin, Olivier Bachem, Massimiliano Ciaramita, Thomas Hofmann |
| 2022 | ICLR | The Role of Pretrained Representations for the OOD Generalization of RL Agents. | Frederik Truble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schlkopf, Stefan Bauer |
| 2021 | ICLR | What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study. | Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphal Marinier, Lonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem |
| 2021 | ICML | Hyperparameter Selection for Imitation Learning. | Lonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphal Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin |
| 2020 | AAAI | 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 |
| 2020 | AAAI | A Commentary on the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2020 | AISTATS | Precision-Recall Curves Using Information Divergence Frontiers. | Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly |
| 2020 | ICLR | Disentangling Factors of Variations Using Few Labels. | Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rtsch, Bernhard Schlkopf, Olivier Bachem |
| 2020 | ICML | Weakly-Supervised Disentanglement Without Compromises. | Francesco Locatello, Ben Poole, Gunnar Rtsch, Bernhard Schlkopf, Olivier Bachem, Michael Tschannen |
| 2020 | ICML | Automatic Shortcut Removal for Self-Supervised Representation Learning. | Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen |
| 2019 | ICLR | Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2019 | ICML | Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. | Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rtsch, Sylvain Gelly, Bernhard Schlkopf, Olivier Bachem |
| 2019 | ICML | High-Fidelity Image Generation With Fewer Labels. | Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly |
| 2018 | AISTATS | One-shot Coresets: The Case of k-Clustering. | Olivier Bachem, Mario Lucic, Silvio Lattanzi |
| 2018 | KDD | Scalable k -Means Clustering via Lightweight Coresets. | Olivier Bachem, Mario Lucic, Andreas Krause |
| 2017 | ICML | Distributed and Provably Good Seedings for k-Means in Constant Rounds. | Olivier Bachem, Mario Lucic, Andreas Krause |
| 2017 | ICML | Uniform Deviation Bounds for k-Means Clustering. | Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause |
| 2016 | AAAI | Approximate K-Means++ in Sublinear Time. | Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause |
| 2016 | AISTATS | Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. | Mario Lucic, Olivier Bachem, Andreas Krause |
| 2016 | ICML | Horizontally Scalable Submodular Maximization. | Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause |
| 2016 | IJCAI | Linear-Time Outlier Detection via Sensitivity. | Mario Lucic, Olivier Bachem, Andreas Krause |
| 2015 | ICML | Coresets for Nonparametric Estimation - the Case of DP-Means. | Olivier Bachem, Mario Lucic, Andreas Krause |