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Found 5 papers, 1 papers with code
Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representation
We analyze this phenomenon and reveal that entity codes, the quantization outcomes for expressing entities, have higher entropy at the code level and Jaccard distance at the codeword level under random entity quantization.
Video traffic identification with novel feature extraction and selection method
Second, to reduce the cost of video traffic identification and select an effective feature subset, the current research proposes an adaptive distribution distance-based feature selection (ADDFS) method, which uses Wasserstein distance to measure the distance between feature distributions.
Neural Architecture Search for Inversion
Over the year, people have been using deep learning to tackle inversion problems, and we see the framework has been applied to build relationship between recording wavefield and velocity (Yang et al., 2016).
Curriculum Learning for Natural Language Understanding
With the great success of pre-trained language models, the pretrain-finetune paradigm now becomes the undoubtedly dominant solution for natural language understanding (NLU) tasks.
An Effective Way to Improve YouTube-8M Classification Accuracy in Google Cloud Platform
Competitors are challenged to develop classification algorithms that assign video-level labels using the new and improved Youtube-8M V2 dataset.
