Niklas Åkerblom

According to our database, Niklas Åkerblom authored at least 11 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Online Learning Models for Vehicle Usage Prediction During COVID-19.

Tobias Lindroth, Axel Svensson, Niklas Åkerblom, Mitra Pourabdollah, Morteza Haghir Chehreghani

IEEE Trans. Intell. Transp. Syst., August, 2024

Tree Ensembles for Contextual Bandits.

Hannes Nilsson, Rikard Johansson, Niklas Åkerblom, Morteza Haghir Chehreghani

CoRR, 2024

A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification.

Fazeleh Sadat Hoseini, Niklas Åkerblom, Morteza Haghir Chehreghani

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Online learning of energy consumption for navigation of electric vehicles.

Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

Artif. Intell., April, 2023

Online learning of network bottlenecks via minimax paths.

Niklas Åkerblom, Fazeleh Sadat Hoseini, Morteza Haghir Chehreghani

Mach. Learn., January, 2023

A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles.

Niklas Åkerblom, Morteza Haghir Chehreghani

Trans. Mach. Learn. Res., 2023

Combinatorial Gaussian Process Bandits in Bayesian Settings: Theory and Application for Energy-Efficient Navigation.

Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani

CoRR, 2023

Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach.

Arman Rahbar, Niklas Åkerblom, Morteza Haghir Chehreghani

CoRR, 2023

2022

An Online Learning Approach for Vehicle Usage Prediction During COVID-19.

Tobias Lindroth, Axel Svensson, Niklas Åkerblom, Mitra Pourabdollah, Morteza Haghir Chehreghani

CoRR, 2022

Passive and Active Learning of Driver Behavior from Electric Vehicles.

Federica Comuni, Christopher Mészáros, Niklas Åkerblom, Morteza Haghir Chehreghani

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

2020

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

Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020