no code implementations • 25 May 2024 • Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Ya'acov Ritov, Mikhail Yurochkin, Yuekai Sun
In particular, it is unclear whether it is possible to align (stronger) LLMs with superhuman capabilities with (weaker) human feedback without degrading their capabilities.
no code implementations • 20 Apr 2024 • Seamus Somerstep, Yuekai Sun, Ya'acov Ritov
Motivated by equilibrium models of labor markets, we develop a formulation of causal strategic classification in which strategic agents can directly manipulate their outcomes.
no code implementations • 16 Jun 2021 • Junhui Cai, Xu Han, Ya'acov Ritov, Linda Zhao
In contrast to the state-of-the-art methods, the proposed methods solve the estimation and testing problem at once with several merits: 1) an accurate sparsity estimation; 2) point estimates with shrinkage/soft-thresholding property; 3) credible intervals for uncertainty quantification; 4) an optimal multiple testing procedure that controls false discovery rate.
no code implementations • 22 Feb 2021 • Debarghya Mukherjee, Moulinath Banerjee, Ya'acov Ritov
In this paper, we present a new model coined SCENTS: Score Explained Non-Randomized Treatment Systems, and a corresponding method that allows estimation of the treatment effect at $\sqrt{n}$ rate in the presence of fairly general forms of confoundedness, when the `score' variable on whose basis treatment is assigned can be explained via certain feature measurements of the individuals under study.
Methodology Statistics Theory Statistics Theory
1 code implementation • 8 Sep 2019 • Hamid Eftekhari, Moulinath Banerjee, Ya'acov Ritov
The problem of statistical inference for regression coefficients in a high-dimensional single-index model is considered.
Statistics Theory Other Statistics Statistics Theory
no code implementations • 26 Jun 2017 • Ya'acov Ritov, Yuekai Sun, Ruofei Zhao
We identify conditional parity as a general notion of non-discrimination in machine learning.