Mar 10, 2018 · Abstract:We present a new machine learning approach to estimate personalized treatment effects in the classical potential outcomes framework ...
A new machine learning approach to estimate personalized treatment effects in the classical potential outcomes framework with binary outcomes is presented, ...
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A Minimax Surrogate Loss Approach to Conditional Difference Estimation · 1 ... We present sparse tree-based and list-based density estimation methods for binary/ ...
Jan 31, 2024 · A Minimax Surrogate Loss Approach to Conditional Difference Estimation. Siong Thye Goh, C. Rudin. 2018, arXiv.org. Deep IV: A Flexible Approach ...
A Minimax Surrogate Loss Approach to Conditional Difference Estimation · 1 ... analysis: Building a better stroke prediction model · 2 code implementations ...
A Minimax Surrogate Loss Approach to Conditional Difference Estimation. We present a new machine learning approach to estimate personalized trea... 0 Siong ...
Supplement for "A Minimax Surrogate Loss Approach to Conditional Difference Estimation". We present a new machine learning approach to estimate whether a ...
This loss function, which we call the minimax-hinge loss, is also different from the classic hinge loss (Figure 2). We emphasize that while the hinge loss is.
We further propose a minimax learning method to learn future-dependent value functions using the new Bellman equation. We obtain the PAC result, which implies ...
We propose a particular implementation of solving our problem based on recent work on efficiently solving conditional mo- ment problems using a reformulation of ...