Sergey Levine
(9 articles)
Policy Gradient Algorithm
Type of RL algorithm that optimizes the policy directly by computing gradients of expected rewards with respect to policy parameters.
Generality: 805
Policy Gradient
Class of algorithms in RL that optimizes the parameters of a policy directly through gradient ascent on expected future rewards.
Generality: 675
Data Efficient Learning
ML approach that requires fewer data to train a functional model.
Generality: 791
TRPO
Trust Region Policy Optimization
Trust Region Policy Optimization
Advanced algorithm used in RL to ensure stable and reliable policy updates by optimizing within a trust region, thus preventing drastic policy changes.
Generality: 635
Imitation Learning
AI technique where models learn to perform tasks by mimicking human behavior or strategies demonstrated in training data.
Generality: 850
Sample Efficiency
Ability of a ML model to achieve high performance with a relatively small number of training samples.
Generality: 815
FSL
Few-Shot Learning
Few-Shot Learning
ML approach that enables models to learn and make accurate predictions from a very small dataset.
Generality: 575
Few Shot
ML technique designed to recognize patterns and make predictions based on a very limited amount of training data.
Generality: 675
PPO
Proximal Policy Optimization
Proximal Policy Optimization
RL algorithm that aims to balance ease of implementation, sample efficiency, and reliable performance by using a simpler but effective update method for policy optimization.
Generality: 670