Niklas Åkerblom — accepted AI-conference papers

2025

Bayesian Analysis of Combinatorial Gaussian Process Bandits

Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani

ICLR 2025poster

We consider the combinatorial volatile Gaussian process (GP) semi-bandit problem. Each round, an agent is provided a set of available base arms and must select a subset of them to maximize the long-term cumulative reward. We study the Bayesian setting and provide novel Bayesian cumulative regret bou…

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2020

An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles

Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

IJCAI 2020poster

Energy-efficient navigation constitutes an important challenge in electric vehicles, due to their limited battery capacity. We employ a Bayesian approach to model the energy consumption at road segments for efficient navigation. In order to learn the model parameters, we develop an online learning f…

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