Bigger, Regularized, Optimistic: scaling for compute and sample-efficient continuous control

25 May 2024

Papers citing "Bigger, Regularized, Optimistic: scaling for compute and sample-efficient continuous control"

20 / 20 papers shown

Title
Active Perception for Tactile Sensing: A Task-Agnostic Attention-Based Approach Tim Schneider Cristiana de Farias Roberto Calandra L. Chen Jan Peters 45 0 0 09 May 2025
Plasticine: Accelerating Research in Plasticity-Motivated Deep Reinforcement Learning Mingqi Yuan Qi Wang Guozheng Ma Bo-wen Li Xin Jin Yunbo Wang Xiaokang Yang Wenjun Zeng D. Tao OffRL AI4CE 33 0 0 24 Apr 2025
Plasticity-Aware Mixture of Experts for Learning Under QoE Shifts in Adaptive Video Streaming Zhiqiang He Zhi Liu 36 0 0 14 Apr 2025
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities Kevin Wang Ishaan Javali Michał Bortkiewicz Tomasz Trzciñski Benjamin Eysenbach SSL OffRL 67 0 0 19 Mar 2025
NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models Mert Albaba Chenhao Li Markos Diomataris Omid Taheri Andreas Krause M. Black VGen 58 0 0 13 Mar 2025
Multi-Task Reinforcement Learning Enables Parameter Scaling Reginald McLean Evangelos Chataroulas Jordan Terry Isaac Woungang Nariman Farsad P. S. Castro LRM 39 0 0 07 Mar 2025
Impoola: The Power of Average Pooling for Image-Based Deep Reinforcement Learning Raphael Trumpp Ansgar Schäfftlein Mirco Theile Marco Caccamo 34 0 0 07 Mar 2025
Eau De $Q$ -Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning Théo Vincent Tim Lukas Faust Yogesh Tripathi Jan Peters Carlo DÉramo 32 0 0 03 Mar 2025
Hyperspherical Normalization for Scalable Deep Reinforcement Learning Hojoon Lee Youngdo Lee Takuma Seno Donghu Kim Peter Stone Jaegul Choo 63 1 0 24 Feb 2025
Massively Scaling Explicit Policy-conditioned Value Functions Nico Bohlinger Jan Peters OffRL 54 0 0 17 Feb 2025
SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning Hojoon Lee Dongyoon Hwang Donghu Kim Hyunseung Kim Jun Jet Tai K. Subramanian Peter R. Wurman Jaegul Choo Peter Stone Takuma Seno OffRL 60 6 0 13 Oct 2024
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL C. Voelcker Marcel Hussing Eric Eaton Amir-massoud Farahmand Igor Gilitschenski 39 1 0 11 Oct 2024
Active Fine-Tuning of Generalist Policies Marco Bagatella Jonas Hübotter Georg Martius Andreas Krause 32 0 0 07 Oct 2024
Simplifying Deep Temporal Difference Learning Matteo Gallici Mattie Fellows Benjamin Ellis B. Pou Ivan Masmitja Jakob Foerster Mario Martin OffRL 51 12 0 05 Jul 2024
Generalizability of experimental studies Federico Matteucci Vadim Arzamasov Jose Cribeiro-Ramallo Marco Heyden Konstantin Ntounas Klemens Bohm 40 0 0 25 Jun 2024
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL Jesse Farebrother Jordi Orbay Q. Vuong Adrien Ali Taïga Yevgen Chebotar ... Sergey Levine Pablo Samuel Castro Aleksandra Faust Aviral Kumar Rishabh Agarwal OffRL 56 55 0 06 Mar 2024
Disentangling the Causes of Plasticity Loss in Neural Networks Clare Lyle Zeyu Zheng Khimya Khetarpal H. V. Hasselt Razvan Pascanu James Martens Will Dabney AI4CE 53 30 0 29 Feb 2024
The Primacy Bias in Deep Reinforcement Learning Evgenii Nikishin Max Schwarzer P. DÓro Pierre-Luc Bacon Aaron C. Courville OnRL 85 178 0 16 May 2022
Learning Pessimism for Robust and Efficient Off-Policy Reinforcement Learning Edoardo Cetin Oya Celiktutan OffRL 29 16 0 07 Oct 2021
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 127 135 0 09 Dec 2019