12 citations · 12 across the 2 of their papers we have counts for
4 papers
Recommendation on a Budget: Column Space Recovery from Partially Observed Entries with Random or Active Sampling
Carolyn Kim, Mohsen Bayati
We analyze alternating minimization for column space recovery of a partially observed, approximately low rank matrix with a growing number of columns and a fixed budget of observat…
Learning Interpretable Models with Causal Guarantees
Carolyn Kim, Osbert Bastani
Machine learning has shown much promise in helping improve the quality of medical, legal, and financial decision-making. In these applications, machine learning models must satisfy…
Interpretability via Model Extraction
Osbert Bastani, Carolyn Kim, Hamsa Bastani
The ability to interpret machine learning models has become increasingly important now that machine learning is used to inform consequential decisions. We propose an approach calle…
Interpreting Blackbox Models via Model Extraction
Osbert Bastani, Carolyn Kim, Hamsa Bastani
Interpretability has become incredibly important as machine learning is increasingly used to inform consequential decisions. We propose to construct global explanations of complex,…