116 citations · 1.1k across the 89 of their papers we have counts for
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What Makes A Good Fisherman? Linear Regression under Self-Selection Bias
Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas +1
In the classical setting of self-selection, the goal is to learn models, simultaneously from observations where is the output of one of under…
A Statistical Taylor Theorem and Extrapolation of Truncated Densities
Constantinos Daskalakis, Vasilis Kontonis, Christos Tzamos +1
We show a statistical version of Taylor's theorem and apply this result to non-parametric density estimation from truncated samples, which is a classical challenge in Statistics \c…
Computationally and Statistically Efficient Truncated Regression
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos +1
We provide a computationally and statistically efficient estimator for the classical problem of truncated linear regression, where the dependent variable and its co…
Learning Ising models from one or multiple samples
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala +1
There have been two separate lines of work on estimating Ising models: (1) estimating them from multiple independent samples under minimal assumptions about the model's interaction…
Efficient Statistics, in High Dimensions, from Truncated Samples
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos +1
We provide an efficient algorithm for the classical problem, going back to Galton, Pearson, and Fisher, of estimating, with arbitrary accuracy the parameters of a multivariate norm…