56 citations · 182 across the 18 of their papers we have counts for
5 papers · 1 filter
Dynamic Decision Frequency with Continuous Options
Amirmohammad Karimi, Jun Jin, Jun Luo +3
In classic reinforcement learning algorithms, agents make decisions at discrete and fixed time intervals. The duration between decisions becomes a crucial hyperparameter, as settin…
HesScale: Scalable Computation of Hessian Diagonals
Mohamed Elsayed, A. Rupam Mahmood
Second-order optimization uses curvature information about the objective function, which can help in faster convergence. However, such methods typically require expensive computati…
Real-Time Reinforcement Learning for Vision-Based Robotics Utilizing Local and Remote Computers
Yan Wang, Gautham Vasan, A. Rupam Mahmood
Real-time learning is crucial for robotic agents adapting to ever-changing, non-stationary environments. A common setup for a robotic agent is to have two different computers simul…
Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation
Qingfeng Lan, Yangchen Pan, Jun Luo +1
Artificial neural networks are promising for general function approximation but challenging to train on non-independent or non-identically distributed data due to catastrophic forg…
A Temporal-Difference Approach to Policy Gradient Estimation
Samuele Tosatto, Andrew Patterson, Martha White +1
The policy gradient theorem (Sutton et al., 2000) prescribes the usage of a cumulative discounted state distribution under the target policy to approximate the gradient. Most algor…