20 citations · 36 across the 3 of their papers we have counts for
6 papers
Modifying Squint for Prediction with Expert Advice in a Changing Environment
Thom Neuteboom, Tim van Erven
We provide a new method for online learning, specifically prediction with expert advice, in a changing environment. In a non-changing environment the Squint algorithm has been desi…
Distributed Online Learning for Joint Regret with Communication Constraints
Dirk van der Hoeven, Hédi Hadiji, Tim van Erven
We consider distributed online learning for joint regret with communication constraints. In this setting, there are multiple agents that are connected in a graph. Each round, an ad…
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning
Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven
We provide a new adaptive method for online convex optimization, MetaGrad, that is robust to general convex losses but achieves faster rates for a broad class of special functions,…
Explaining Predictions by Approximating the Local Decision Boundary
Georgios Vlassopoulos, Tim van Erven, Henry Brighton +1
Constructing accurate model-agnostic explanations for opaque machine learning models remains a challenging task. Classification models for high-dimensional data, like images, are o…
Second-order Quantile Methods for Experts and Combinatorial Games
Wouter M. Koolen, Tim van Erven
We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expe…
Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma
Tim van Erven, Peter Grunwald, Steven de Rooij
Bayesian model averaging, model selection and its approximations such as BIC are generally statistically consistent, but sometimes achieve slower rates og convergence than other me…