Events

Talk given by Gilmer Valdes, associate professor in the Departments of Radiation Oncology, Epidemiology and Biostatistics at UCSF Abstract: Many regression and classification procedures fit a function f(x;w) of predictor variables x to data 〖{x_i,y_i}〗_1^N based on some loss criterion L(y,f(x;w)). Often, regularization is applied to improve accuracy by placing a constraint P(w)≤t on the […]