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Found 5 papers, 1 papers with code
Comparative Study on the Performance of Categorical Variable Encoders in Classification and Regression Tasks
This study broadly classifies machine learning models into three categories: 1) ATI models that implicitly perform affine transformations on inputs, such as multi-layer perceptron neural network; 2) Tree-based models that are based on decision trees, such as random forest; and 3) the rest, such as kNN.
COVER: A Heuristic Greedy Adversarial Attack on Prompt-based Learning in Language Models
Prompt-based learning has been proved to be an effective way in pre-trained language models (PLMs), especially in low-resource scenarios like few-shot settings.
Local-Adaptive Face Recognition via Graph-based Meta-Clustering and Regularized Adaptation
Leveraging the environment-specific local data after the deployment of the initial global model, LaFR aims at getting optimal performance by training local-adapted models automatically and un-supervisely, as opposed to fixing their initial global model.
ReDA:Reinforced Differentiable Attribute for 3D Face Reconstruction
The key challenge for 3D face shape reconstruction is to build the correct dense face correspondence between the deformable mesh and the single input image.
A deep-learning-based approach for fast and robust steel surface defects classification
Automatic visual recognition of steel surface defects provides critical functionality to facilitate quality control of steel strip production.
