This paper proposes novel phase retrieval algorithms for maximum likelihood (ML)
estimation from measurements following independent Poisson distributions in very low …

Logistic regression training over encrypted data has been an attractive idea to security
concerns for years. In this paper, we propose a faster gradient variant called $\texttt …

Nan Laird has an enormous and growing impact on computational statistics. Her paper with
Dempster and Rubin on the expectation‐maximisation (EM) algorithm is the second most …

It might be inadequate for the line search technique for Newton's method to use only one
floating point number. A column vector of the same size as the gradient might be better than …

Estimating multinomial models with many fixed effects faces prohibitive computational
challenges. We develop a new method based on the Minorization-Maximization (MM) …

[ES] Con los avances tecnológicos también se ha generado un crecimiento masivo en la
cantidad y variedad de datos, esto brinda la oportunidad de tener una comprensión más …

Logistic regression training over encrypted data has been an attractive idea to security
concerns for years. In this paper, we propose a faster gradient variant called quadratic …