Search Results for author:
Found 5 papers, 2 papers with code
A Reinforcement Learning based Reset Policy for CDCL SAT Solvers
In most solvers, variable activities are preserved across restart boundaries, resulting in solvers continuing to search parts of the assignment tree that are not far from the one immediately prior to a restart.
REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Accelerating learning processes for complex tasks by leveraging previously learned tasks has been one of the most challenging problems in reinforcement learning, especially when the similarity between source and target tasks is low.
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground with Human-in-the-loop
We present the Battlesnake Challenge, a framework for multi-agent reinforcement learning with Human-In-the-Loop Learning (HILL).
Multi-agent Reinforcement Learning
reinforcement-learning
+1
YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection
As such, there has been growing research interest in the design of efficient deep neural network architectures catered for edge and mobile usage.
A Computationally Efficient Pipeline Approach to Full Page Offline Handwritten Text Recognition
Offline handwriting recognition with deep neural networks is usually limited to words or lines due to large computational costs.
