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Adaptive learning of density ratios in RKHS
Estimating the ratio of two probability densities from finitely many observations of the densities is a central problem in machine learning and statistics with applications in two-sample testing, divergence estimation, generative modeling, covariate shift adaptation, conditional density estimation, and novelty detection.
Optimal-order convergence of Nesterov acceleration for linear ill-posed problems
We show that Nesterov acceleration is an optimal-order iterative regularization method for linear ill-posed problems provided that a parameter is chosen accordingly to the smoothness of the solution.
Numerical Analysis Numerical Analysis
