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Found 8 papers, 6 papers with code
Pragmatic Fairness: Developing Policies with Outcome Disparity Control
We introduce a causal framework for designing optimal policies that satisfy fairness constraints.
Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach
We propose a kernel-based nonparametric estimator for the causal effect when the cause is corrupted by error.
Beyond Impossibility: Balancing Sufficiency, Separation and Accuracy
Among the various aspects of algorithmic fairness studied in recent years, the tension between satisfying both \textit{sufficiency} and \textit{separation} -- e. g. the ratios of positive or negative predictive values, and false positive or false negative rates across groups -- has received much attention.
Operationalizing Complex Causes: A Pragmatic View of Mediation
We examine the problem of causal response estimation for complex objects (e. g., text, images, genomics).
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
In particular, we provide a unifying view of two-stage and moment restriction approaches for solving this problem in a nonlinear setting.
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice
Necessity and sufficiency are the building blocks of all successful explanations.
Differentiable Causal Backdoor Discovery
Discovering the causal effect of a decision is critical to nearly all forms of decision-making.
Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops
While humor is often thought to be beyond the reach of Natural Language Processing, we show that several aspects of single-word humor correlate with simple linear directions in Word Embeddings.
