= Victor Chernozhukov
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<Victor Chernozhukov> works on <econometrics> and statistical inference with <machine learning>. With <Alexandre Belloni> and <Lie Wang>, he developed the <Square-root Lasso>, whose penalty calibration does not require knowing the noise scale.<Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming by Alexandre Belloni and others>[Abstract and section 1]{ref}
He also coauthored work on <double machine learning>. Predicting an outcome accurately does not by itself estimate a <causal effect> accurately: errors in fitted nuisance functions can bias the target parameter. An orthogonal estimating equation reduces first-order sensitivity to those errors, while <cross-fitting> separates training observations from score evaluation. Valid <confidence intervals> still require the paper's identification and convergence assumptions.<Double Debiased Machine Learning for Treatment and Structural Parameters by Victor Chernozhukov and others>[2017 version, sections 2.1 and 3; section 5.1]{ref}
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