42 citations · 136 across the 14 of their papers we have counts for
14 papers
Operationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry
Serena Wang, Stephen Bates, P. M. Aronow +1
From the social sciences to machine learning, it has been well documented that metrics to be optimized are not always aligned with social welfare. In healthcare, Dranove et al. (20…
Robust Distillation for Worst-class Performance
Serena Wang, Harikrishna Narasimhan, Yichen Zhou +3
Knowledge distillation has proven to be an effective technique in improving the performance a student model using predictions from a teacher model. However, recent work has shown t…
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence
Ghassen Jerfel, Serena Wang, Clara Fannjiang +3
Variational Inference (VI) is a popular alternative to asymptotically exact sampling in Bayesian inference. Its main workhorse is optimization over a reverse Kullback-Leibler diver…
Multi-Source Causal Inference Using Control Variates
Wenshuo Guo, Serena Wang, Peng Ding +2
While many areas of machine learning have benefited from the increasing availability of large and varied datasets, the benefit to causal inference has been limited given the strong…
Regularization Strategies for Quantile Regression
Taman Narayan, Serena Wang, Kevin Canini +1
We investigate different methods for regularizing quantile regression when predicting either a subset of quantiles or the full inverse CDF. We show that minimizing an expected pinb…
Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty
Wenshuo Guo, Mihaela Curmei, Serena Wang +2
We study the problem of finding equilibrium strategies in multi-agent games with incomplete payoff information, where the payoff matrices are only known to the players up to some b…