21 citations · 21 across the 1 of their papers we have counts for
3 papers
Breaking Feedback Loops in Recommender Systems with Causal Inference
Karl Krauth, Yixin Wang, Michael I. Jordan
Recommender systems play a key role in shaping modern web ecosystems. These systems alternate between (1) making recommendations (2) collecting user responses to these recommendati…
Recommendation Systems with Distribution-Free Reliability Guarantees
Anastasios N. Angelopoulos, Karl Krauth, Stephen Bates +2
When building recommendation systems, we seek to output a helpful set of items to the user. Under the hood, a ranking model predicts which of two candidate items is better, and we…
AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models
Karl Krauth, Edwin V. Bonilla, Kurt Cutajar +1
We investigate the capabilities and limitations of Gaussian process models by jointly exploring three complementary directions: (i) scalable and statistically efficient inference;…