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Found 6 papers, 2 papers with code
Collective Counterfactual Explanations via Optimal Transport
To address these issues, our work proposes a collective approach for formulating counterfactual explanations, with an emphasis on utilizing the current density of the individuals to inform the recommended actions.
What Makes ImageNet Look Unlike LAION
ImageNet was famously created from Flickr image search results.
Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care
By disentangling accurate and approximated rewards through action pruning, potential distortions of the main objective are minimized, all while enabling the extraction of valuable information from intermediate signals that can guide the learning process.
A Theory of Dynamic Benchmarks
Dynamic benchmarks interweave model fitting and data collection in an attempt to mitigate the limitations of static benchmarks.
Sequential Nature of Recommender Systems Disrupts the Evaluation Process
Datasets are often generated in a sequential manner, where the previous samples and intermediate decisions or interventions affect subsequent samples.
Collaborative Filtering with Smooth Reconstruction of the Preference Function
The performance of the method is evaluated on two benchmark datasets (ML-100k and ML-1M).
