Incorporating Parameter Constraints in GLMs
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Parameter Estimation of Generalized Linear Models without Assuming their Link Function
Canonical generalized linear models (GLM) are specified by a finite dimensional vector and a monotonically increasing function called the link function. Standard parameter estimation techniques hold the link function fixed and optimizes over the parameter vector. We propose a parameter-recovery facilitating, jointly-convex, regularized loss functional that is optimized globally over the vector ...
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