Hengshuai Yao

Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings

2020

Significant progress has been made recently in developing few-shot object segmentation methods. Learning is shown to be successful in few-shot segmentation settings, using pixel-level, scribbles and bounding box supervision. This paper takes another approach, i.e., …

Variance-Reduced Off-Policy Memory-Efficient Policy Search

2020 · arXiv (Cornell University)

Off-policy policy optimization is a challenging problem in reinforcement learning (RL). The algorithms designed for this problem often suffer from high variance in their estimators, which results in poor sample efficiency, and have issues with …