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Found 5 papers, 1 papers with code
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning
Graph learning plays a pivotal role and has gained significant attention in various application scenarios, from social network analysis to recommendation systems, for its effectiveness in modeling complex data relations represented by graph structural data.
SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems
Recently deep neural networks (DNNs) have achieved tremendous success for object detection in overhead (e. g., satellite) imagery.
BERT-based Chinese Text Classification for Emergency Domain with a Novel Loss Function
This paper proposes an automatic Chinese text categorization method for solving the emergency event report classification problem.
Pretrain Soft Q-Learning with Imperfect Demonstrations
Pretraining reinforcement learning methods with demonstrations has been an important concept in the study of reinforcement learning since a large amount of computing power is spent on online simulations with existing reinforcement learning algorithms.
