Exploratory Mediation Analysis via Regularization

Contraction analysis of switched systems via regularization

In this paper we study incremental stability and convergence of switched (bimodal) Filippov systems via contraction analysis. In particular, by using results on regularization of switched dynamical systems we derive sufficient conditions for convergence of any two trajectories of the Filippov system between each other within some region of interest. We then apply these conditions to the study o...

Identifying Mechanisms behind Policy Interventions via Causal Mediation Analysis

Causal analysis in program evaluation has largely focused on the assessment of policy effectiveness. That is, researchers typically study whether a program has a causal effect on the outcome of interest. However, it is often of scientific and practical importance to also explain why such a causal relationship arises. In this paper, we introduce causal mediation analysis, a statistical framework...

Identifying Mechanisms behind Policy Interventions via Causal Mediation Analysis

Causal analysis in program evaluation has primarily focused on the question about whether or not a program, or package of policies, has an impact on the targeted outcome of interest. However, it is often of scientific and practical importance to also explain why such impacts occur. In this paper, we introduce causal mediation analysis, a statistical framework for analyzing causal mechanisms tha...

Regularization via Mass Transportation

The goal of regression and classification methods in supervised learning is to minimize the empirical risk, that is, the expectation of some loss function quantifying the prediction error under the empirical distribution. When facing scarce training data, overfitting is typically mitigated by adding regularization terms to the objective that penalize hypothesis complexity. In this paper we intr...

Complexity Regularization via Localized