Search Results for author:
Found 7 papers, 2 papers with code
Allocation Requires Prediction Only if Inequality Is Low
Algorithmic predictions are emerging as a promising solution concept for efficiently allocating societal resources.
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 sparse rewards and frequently measured reward proxies through action pruning, our work represents a step towards developing reliable policies that effectively harness the wealth of available information in data-intensive critical care environments.
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).
