In: Bioinformatics, 2018, vol. 34, no. 22, p. 3843-3848
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In: Calculus of Variations and Partial Differential Equations, 2015, vol. 52, no. 3-4, p. 469-488
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In: Biometrika, 2017, vol. 104, no. 1, p. 243-249
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In: Machine Learning, 2015, vol. 99, no. 3, p. 373-409
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In: Journal of Econometric Methods, 2019, vol. 8, no. 1, p. 1-20
Using a sequential conditional independence assumption, this paper discusses fully nonparametric estimation of natural direct and indirect causal effects in causal mediation analysis based on inverse probability weighting. We propose estimators of the average indirect effect of a binary treatment, which operates through intermediate variables (or mediators) on the causal path between the...
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In: Journal of Business and Economic Statistics, 2020, vol. 38, no. 1, p. 183-200
This article investigates the finite sample properties of a range of inference methods for propensity score-based matching and weighting estimators frequently applied to evaluate the average treatment effect on the treated. We analyze both asymptotic approximations and bootstrap methods for computing variances and confidence intervals in our simulation designs, which are based on German...
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In: Journal für die reine und angewandte Mathematik, 2020, vol. 2020, no. 763, p. 79–109
The Dehn function measures the area of minimal discs that fill closed curves in a space; it is an important invariant in analysis, geometry, and geometric group theory. There are several equivalent ways to define the Dehn function, varying according to the type of disc used. In this paper, we introduce a new definition of the Dehn function and use it to prove several theorems. First, we...
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In: Formal Methods in System Design, 2014, vol. 45, no. 1, p. 1-41
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In: Communications in Mathematical Physics, 2014, vol. 332, no. 3, p. 1167-1202
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In: Proceedings of the 13th International Conference on Semantic Systems, 2017, p. 65–72
Webpages are an abundant source of textual information with manually annotated entity links, and are often used as a source of training data for a wide variety of machine learning NLP tasks. However, manual annotations such as those found on Wikipedia are sparse, noisy, and biased towards popular entities. Existing entity linking systems deal with those issues by relying on simple statistics...
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