3 accepted papers
Independent Metropolis–Hastings (IMH) algorithms are widely used in Bayesian inference, but their efficiency deteriorates when proposal distributions are constructed from inaccurate or approximate models. We introduce Proximal-IMH, an IMH method that enhances proposal distributions through a proxima…
We investigate theory and algorithms for pool-based active learning for multiclass classification using multinomial logistic regression. Using finite sample analysis, we prove that the Fisher Information Ratio (FIR) lower and upper bounds the excess risk. Based on our theoretical analysis, we pro…
It has been observed that residual networks can be viewed as the explicit Euler discretization of an Ordinary Differential Equation (ODE). This observation motivated the introduction of so-called Neural ODEs, in which other discretization schemes and/or adaptive time stepping techniques can be used…