Morteza Haghir Chehreghani
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Showing 16 publications
Deep Q-learning: a robust control approach
Passive and Active Learning of Driver Behavior from Electric Vehicles
Online Learning of Network Bottlenecks via Minimax Paths
Reliable Agglomerative Clustering
Shallow Node Representation Learning using Centrality Indices
Online Learning of Energy Consumption for Navigation of Electric Vehicles
Vehicle Motion Trajectories Clustering via Embedding Transitive Relations
Model-Centric and Data-Centric Aspects of Active Learning for Deep Neural Networks
An online learning framework for energy-efficient navigation of electric vehicles
Unsupervised representation learning with Minimax distance measures
Learning representations from dendrograms
Accelerated proximal incremental algorithm schemes for non-strongly convex functions
Generation of Driving Scenario Trajectories with Generative Adversarial Networks
A Non-Convex Optimization Approach to Correlation Clustering
Efficient context-aware K-nearest neighbor search
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Showing 4 research projects
Energy-based models for supervised deep neural networks and their applications
Adaptive Neural Controller for Future Renewable Fuels
Modelling and optimization of energy management systems for plug-in hybrid vehicles
AI-assisted real-time digital twin for electric drivetrains