18 citations · 33 across the 4 of their papers we have counts for
5 papers · 1 filter
Minimax rates without the fixed sample size assumption
Alisa Kirichenko, Peter Grünwald
We generalize the notion of minimax convergence rate. In contrast to the standard definition, we do not assume that the sample size is fixed in advance. Allowing for varying sample…
Safe-Bayesian Generalized Linear Regression
Rianne de Heide, Alisa Kirichenko, Nishant Mehta +1
We study generalized Bayesian inference under misspecification, i.e. when the model is 'wrong but useful'. Generalized Bayes equips the likelihood with a learning rate . We show…
Minimax lower bounds for function estimation on graphs
Alisa Kirichenko, Harry van Zanten
We study minimax lower bounds for function estimation problems on large graph when the target function is smoothly varying over the graph. We derive minimax rates in the context of…
Estimating a smooth function on a large graph by Bayesian Laplacian regularisation
Alisa Kirichenko, Harry van Zanten
We study a Bayesian approach to estimating a smooth function in the context of regression or classification problems on large graphs. We derive theoretical results that show how as…
Optimality of Poisson processes intensity learning with Gaussian processes
Alisa Kirichenko, Harry van Zanten
In this paper we provide theoretical support for the so-called "Sigmoidal Gaussian Cox Process" approach to learning the intensity of an inhomogeneous Poisson process on a -dime…