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Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets
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. As a…
On conditional parity as a notion of non-discrimination in machine learning
Ya'acov Ritov, Yuekai Sun, Ruofei Zhao
We identify conditional parity as a general notion of non-discrimination in machine learning. In fact, several recently proposed notions of non-discrimination, including a few coun…
Sparse Empirical Bayes Analysis (SEBA)
Natalia Bochkina, Ya'acov Ritov
We consider a joint processing of independent sparse regression problems. Each is based on a sample of \iid observations from $y_{i1}=x…
LLE with low-dimensional neighborhood representation
Yair Goldberg, Ya'acov Ritov
The local linear embedding algorithm (LLE) is a non-linear dimension-reducing technique, widely used due to its computational simplicity and intuitive approach. LLE first linearly…
Manifold Learning: The Price of Normalization
Y. Goldberg, A. Zakai, D. Kushnir +1
We analyze the performance of a class of manifold-learning algorithms that find their output by minimizing a quadratic form under some normalization constraints. This class consist…