Uncertainty assessment in High-dimensional Regression

Uncertainty assessment in High-dimensional Regression

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Nov 3, 2014, 03:00 PM - 04:00 PM | 521 Cory Hall | Happening As Scheduled
Adel Javanmard, EECS, UC Berkeley & EE, Stanford
Abstract: Fitting high-dimensional statistical models often requires the use of non-linear parameter estimation procedures. As a consequence, it is generally impossible to obtain an exact characterization of the probability distribution of the parameter estimates. Concretely, no commonly accepted procedure exists for computing classical measures of uncertainty and statistical significance like...