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Found 4 papers, 1 papers with code
Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Paths
Instead of using black-box models, such as neural networks, we propose to focus on tree-based LTR models, from which we can extract the ground truth feature importance scores using decision paths.
Evaluating Local Explanations using White-box Models
Evaluating explanation techniques using human subjects is costly, time-consuming and can lead to subjectivity in the assessments.
Fashion Landmark Detection and Category Classification for Robotics
Research on automated, image based identification of clothing categories and fashion landmarks has recently gained significant interest due to its potential impact on areas such as robotic clothing manipulation, automated clothes sorting and recycling, and online shopping.
Advances in Variational Inference
Many modern unsupervised or semi-supervised machine learning algorithms rely on Bayesian probabilistic models.
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