ICML 2023 Workshop Frontiers4LCD Submissions

Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport
Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian FATRAS, Guy Wolf, Yoshua Bengio
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
In-Context Decision-Making from Supervised Pretraining
Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Statistics estimation in neural network training: a recursive identification approach
Ruth Crasto, Xuchan Bao, Roger Baker Grosse
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Learning to Optimize with Recurrent Hierarchical Transformers
Abhinav Moudgil, Boris Knyazev, Guillaume Lajoie, Eugene Belilovsky
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Fixed-Budget Hypothesis Best Arm Identification: On the Information Loss in Experimental Design
Masahiro Kato, Masaaki Imaizumi, Takuya Ishihara, Toru Kitagawa
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Unbalanced Optimal Transport meets Sliced-Wasserstein
Thibault Sejourne, Clément Bonet, Kilian FATRAS, Kimia Nadjahi, Nicolas Courty
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Improved sampling via learned diffusions
Lorenz Richter, Julius Berner, Guan-Horng Liu
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Transport, VI, and Diffusions
Francisco Vargas, Nikolas Nüsken
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Stability of Multi-Agent Learning: Convergence in Network Games with Many Players
Aamal Hussain, Dan Leonte, Francesco Belardinelli, Georgios Piliouras
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Limited Information Opponent Modeling
Yongliang Lv, YAN ZHENG, jianye Hao
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Game Theoretic Neural ODE Optimizer
Panagiotis Theodoropoulos, Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
A neural RDE approach for continuous-time non-Markovian stochastic control problems
Melker Höglund, Emilio Ferrucci, Camilo Hernández, Aitor Muguruza Gonzalez, Cristopher Salvi, Leandro Sánchez-Betancourt, Yufei Zhang
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
On First-Order Meta-Reinforcement Learning with Moreau Envelopes
Taha Toghani, Sebastian Perez-Salazar, Cesar A Uribe
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Vector Quantile Regression on Manifolds
Marco Pegoraro, Sanketh Vedula, Aviv A. Rosenberg, Irene Tallini, Emanuele Rodolà, Alexander Bronstein
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Learning with Learning Awareness using Meta-Values
Tim Cooijmans, Milad Aghajohari, Aaron Courville
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Kernel Mirror Prox and RKHS Gradient Flow for Mixed Functional Nash Equilibrium
Pavel Dvurechensky, Jia-Jie Zhu
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Simulation-Free Schrödinger Bridges via Score and Flow Matching
Alexander Tong, Nikolay Malkin, Kilian FATRAS, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Latent Space Editing in Transformer-Based Flow Matching
Vincent Tao Hu, David W Zhang, Meng Tang, Pascal Mettes, Deli Zhao, Cees G. M. Snoek
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Structured State Space Models for In-Context Reinforcement Learning
Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Nicolaus Foerster, Satinder Singh, Feryal Behbahani
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Maximum State Entropy Exploration using Predecessor and Successor Representations
Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
PAC-Bayesian Bounds for Learning LTI-ss systems with Input from Empirical Loss
Deividas Eringis, john leth, Rafal Wisniewski, Zheng-Hua Tan, Mihaly Petreczky
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Ratsch, Guy Tennenholtz
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Preventing Reward Hacking with Occupancy Measure Regularization
Cassidy Laidlaw, Shivam Singhal, Anca Dragan
- Published: 19 Jun 2023, Last Modified: 25 Jul 2023
- Frontiers4LCD
- Readers: Everyone
Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures
Hao Liang, Zhi-Quan Luo
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone
AbODE: Ab initio antibody design using conjoined ODEs
Yogesh Verma, Markus Heinonen, Vikas Garg
- Published: 19 Jun 2023, Last Modified: 09 Jul 2023
- Frontiers4LCD
- Readers: Everyone