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Found 5 papers, 1 papers with code
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks
We find that SHAP exhibits lower variance in sparse segments of the data compared to LIME.
On Negative Sampling for Audio-Visual Contrastive Learning from Movies
The abundance and ease of utilizing sound, along with the fact that auditory clues reveal a plethora of information about what happens in a scene, make the audio-visual space an intuitive choice for representation learning.
Watching Too Much Television is Good: Self-Supervised Audio-Visual Representation Learning from Movies and TV Shows
The abundance and ease of utilizing sound, along with the fact that auditory clues reveal so much about what happens in the scene, make the audio-visual space a perfectly intuitive choice for self-supervised representation learning.
Control Variates for Slate Off-Policy Evaluation
We study the problem of off-policy evaluation from batched contextual bandit data with multidimensional actions, often termed slates.
Off-Policy Evaluation of Slate Policies under Bayes Risk
We study the problem of off-policy evaluation for slate bandits, for the typical case in which the logging policy factorizes over the slots of the slate.
