Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

Yuhuai Wu, Elman Mansimov, Roger B. Grosse, Shun Liao, Jimmy Ba

Nov-21-2025, 07:08:24 GMT–Neural Information Processing Systems

In this work, we propose to apply trust region optimization to deep reinforcement learning using a recently proposed Kronecker-factored approximation to the curvature.

approximation, machine learning, reinforcement learning, (16 more...)

Neural Information Processing Systems

Nov-21-2025, 07:08:24 GMT

Conferences PDF

Country:
- Asia > Middle East
  - Jordan (0.04)
- North America
  - Canada > Ontario
    - Toronto (0.15)
  - United States > California
    - Los Angeles County > Long Beach (0.04)

Industry:
- Leisure & Entertainment > Games (0.49)

Technology:
- Information Technology > Artificial Intelligence > Machine Learning
  - Neural Networks (1.00)
  - Reinforcement Learning (1.00)
  - Statistical Learning > Gradient Descent (0.30)

Duplicate Docs Excel Report

Title
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

Similar Docs Excel Report more

Title	Similarity	Source
None found