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Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks
Combinatorial optimization finds an optimal solution within a discrete set of variables and constraints.
Spatial Cross-Attention Improves Self-Supervised Visual Representation Learning
Unsupervised representation learning methods like SwAV are proved to be effective in learning visual semantics of a target dataset.
Extending Momentum Contrast with Cross Similarity Consistency Regularization
Contrastive self-supervised representation learning methods maximize the similarity between the positive pairs, and at the same time tend to minimize the similarity between the negative pairs.
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