Asia
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
These results confirm our proposed LEHD model can significantly improve the state-of-the-art performance for constructive NCO.
VideoMAE: MaskedAutoencodersareData-Efficient LearnersforSelf-SupervisedVideoPre-Training
Transformer [70]has brought significant progress in natural language processing [17,7,54]. The vision transformer [20] also improves a series of computer vision tasks including image classification [66,88], object detection [8,37], semantic segmentation [80], object tracking [13,16], and video recognition [6,3].
DifferentiallyPrivateFederatedBayesian OptimizationwithDistributedExploration
Unfortunately,FTS[12] is not amenable to a straightforward integration of the general DP framework [45] (Sec.
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model: Supplementary Material Di Wang
In addition, only the foreground categories are considered.
