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Improving Computational Efficiency in Visual Reinforcement Learning via
  Stored Embeddings

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings

4 March 2021
Lili Chen
Kimin Lee
A. Srinivas
Pieter Abbeel
    OffRL
ArXivPDFHTML

Papers citing "Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings"

9 / 9 papers shown
Title
Uncertainty-aware transfer across tasks using hybrid model-based
  successor feature reinforcement learning
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning
Parvin Malekzadeh
Ming Hou
Konstantinos N. Plataniotis
51
1
0
16 Oct 2023
Actively Learning Costly Reward Functions for Reinforcement Learning
Actively Learning Costly Reward Functions for Reinforcement Learning
André Eberhard
Houssam Metni
G. Fahland
A. Stroh
Pascal Friederich
OffRL
35
0
0
23 Nov 2022
Does Self-supervised Learning Really Improve Reinforcement Learning from
  Pixels?
Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
Xiang Li
Jinghuan Shang
Srijan Das
Michael S. Ryoo
SSL
27
31
0
10 Jun 2022
Multi-Source Transfer Learning for Deep Model-Based Reinforcement
  Learning
Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning
Remo Sasso
M. Sabatelli
M. Wiering
49
9
0
28 May 2022
Memory-efficient Reinforcement Learning with Value-based Knowledge
  Consolidation
Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation
Qingfeng Lan
Yangchen Pan
Jun Luo
A. R. Mahmood
OffRL
29
7
0
22 May 2022
On The Transferability of Deep-Q Networks
On The Transferability of Deep-Q Networks
M. Sabatelli
Pierre Geurts
37
2
0
06 Oct 2021
Dropout Q-Functions for Doubly Efficient Reinforcement Learning
Dropout Q-Functions for Doubly Efficient Reinforcement Learning
Takuya Hiraoka
Takahisa Imagawa
Taisei Hashimoto
Takashi Onishi
Yoshimasa Tsuruoka
11
105
0
05 Oct 2021
Decoupling Representation Learning from Reinforcement Learning
Decoupling Representation Learning from Reinforcement Learning
Adam Stooke
Kimin Lee
Pieter Abbeel
Michael Laskin
SSL
DRL
286
341
0
14 Sep 2020
What is the State of Neural Network Pruning?
What is the State of Neural Network Pruning?
Davis W. Blalock
Jose Javier Gonzalez Ortiz
Jonathan Frankle
John Guttag
191
1,027
0
06 Mar 2020
1