Paavo Parmas

According to our database, Paavo Parmas authored at least 8 papers between 2018 and 2024.

Collaborative distances:

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

2024

Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form.

Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai, Kenta Hoshino, Yohei Hosoe, Kazumi Kasaura, Masashi Hamaya, Paavo Parmas, Yutaka Matsuo

CoRR, 2024

2023

Model-based Reinforcement Learning with Scalable Composite Policy Gradient Estimators.

Paavo Parmas, Takuma Seno, Yuma Aoki

Proceedings of the International Conference on Machine Learning, 2023

2022

Proppo: a Message Passing Framework for Customizable and Composable Learning Algorithms.

Paavo Parmas, Takuma Seno

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

2021

A unified view of likelihood ratio and reparameterization gradients.

Paavo Parmas, Masashi Sugiyama

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients.

Daniel Hennes, Dustin Morrill, Shayegan Omidshafiei, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Paavo Parmas, Edgar A. Duéñez-Guzmán, Karl Tuyls

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

A unified view of likelihood ratio and reparameterization gradients and an optimal importance sampling scheme.

Paavo Parmas, Masashi Sugiyama

CoRR, 2019

2018

Total stochastic gradient algorithms and applications in reinforcement learning.

Paavo Parmas

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos.

Paavo Parmas, Carl Edward Rasmussen, Jan Peters, Kenji Doya

Proceedings of the 35th International Conference on Machine Learning, 2018