9 citations · 16 across the 4 of their papers we have counts for
4 papers
A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification
Fazeleh Hoseini, Niklas Åkerblom, Morteza Haghir Chehreghani
Bottleneck identification is a challenging task in network analysis, especially when the network is not fully specified. To address this task, we develop a unified online learning…
Online Learning of Network Bottlenecks via Minimax Paths
Niklas Åkerblom, Fazeleh Sadat Hoseini, Morteza Haghir Chehreghani
In this paper, we study bottleneck identification in networks via extracting minimax paths. Many real-world networks have stochastic weights for which full knowledge is not availab…
A Generic Framework for Clustering Vehicle Motion Trajectories
Fazeleh S. Hoseini, Sadegh Rahrovani, Morteza Haghir Chehreghani
The development of autonomous vehicles requires having access to a large amount of data in the concerning driving scenarios. However, manual annotation of such driving scenarios is…
Memory-Efficient Sampling for Minimax Distance Measures
Fazeleh Sadat Hoseini, Morteza Haghir Chehreghani
Minimax distance measure extracts the underlying patterns and manifolds in an unsupervised manner. The existing methods require a quadratic memory with respect to the number of obj…