Search Results for author:
Found 5 papers, 1 papers with code
Context Matters: Leveraging Spatiotemporal Metadata for Semi-Supervised Learning on Remote Sensing Images
In this paper, we propose to exploit spatiotemporal metainformation in SSL to improve the quality of pseudo-labels and, therefore, the final model performance.
Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learning
In this paper, we propose a novel approach to handle allocation constraints based on a decomposition of the constraint action space into a set of unconstrained allocation problems.
Efficient Parking Search using Shared Fleet Data
The problem has to consider uncertainty as available parking spots might not remain available until arrival due to other vehicles also claiming spots in the meantime.
Spatial-Aware Deep Reinforcement Learning for the Traveling Officer Problem
Furthermore, we propose a novel message-passing module for learning future inter-action correlations in the given environment.
MapFormer: Boosting Change Detection by Using Pre-change Information
Our approach outperforms existing change detection methods by an absolute 11. 7\% and 18. 4\% in terms of binary change IoU on DynamicEarthNet and HRSCD, respectively.
