Morteza Haghir Chehreghani
Professor in Artificial Intelligence (AI) and Machine Learning at the Department of Computer Science and Engineering, Data Science and AI Division. Also, PI of the Machine Learning and Decision Making Lab.
Showing 53 publications
Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach
Mining transactional tree databases under homeomorphism
Utilizing reinforcement learning for de novo drug design
A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification
A unified active learning framework for annotating graph data for regression task
A GREAT Architecture for Edge-Based Graph Problems Like TSP
Correlation Clustering with Active Learning of Pairwise Similarities
Tree Ensembles for Contextual Bandits
Hierarchical Correlation Clustering and Tree Preserving Embedding
Online Learning Models for Vehicle Usage Prediction During COVID-19
Online Learning of Network Bottlenecks via Minimax Paths
Do Kernel and Neural Embeddings Help in Training and Generalization?
Deep Q-learning: a robust control approach
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories
Online Learning of Energy Consumption for Navigation of Electric Vehicles
Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework
De novo generated combinatorial library design
Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction
Efficient Online Decision Tree Learning with Active Feature Acquisition
Non-uniform Sampling Methods for Large Itemset Mining
Batch Mode Deep Active Learning for Regression on Graph Data
Shift of pairwise similarities for data clustering
Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes
A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles
Autonomous Drug Design with Multi-Armed Bandits
A unified framework for online trip destination prediction
On Using Node Indices and Their Correlations for Fake Account Detection
Graph Clustering Using Node Embeddings: An Empirical Study
Active learning of driving scenario trajectories
Efficient Optimization of Dominant Set Clustering with Frank-Wolfe Algorithms
Analysis of Knowledge Transfer in Kernel Regime
Passive and Active Learning of Driver Behavior from Electric Vehicles
Memory-Efficient Minimax Distance Measures
Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction
Controlling gene expression with deep generative design of regulatory DNA
TEP-GNN: Accurate Execution Time Prediction of Functional Tests Using Graph Neural Networks
Trip Prediction by Leveraging Trip Histories from Neighboring Users
Reliable Agglomerative Clustering
Model-Centric and Data-Centric Aspects of Active Learning for Deep Neural Networks
Shallow Node Representation Learning using Centrality Indices
Vehicle Motion Trajectories Clustering via Embedding Transitive Relations
Generation of Driving Scenario Trajectories with Generative Adversarial Networks
Unsupervised representation learning with Minimax distance measures
An online learning framework for energy-efficient navigation of electric vehicles
Accelerated proximal incremental algorithm schemes for non-strongly convex functions
Learning representations from dendrograms
A Non-Convex Optimization Approach to Correlation Clustering
Lifelong learning starting from zero
Efficient context-aware K-nearest neighbor search
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Showing 12 research projects
Cooperative Calibration for Enhanced Localization Services in Transport
Onsite Array Calibration for Joint Localization and Communication Systems
Digital Twin for Energy Prediction
ADMOL: A Generic Framework for Active Decision Making within Online Learning
LEAR: Robust LEArning methods for electric vehicle Route selection
Energy-efficient autopilot (EcoPilot)
Energy-based models for supervised deep neural networks and their applications
Adaptive Neural Controller for Future Renewable Fuels
Real-Time Robust and AdaptIve Learning in ElecTric VEhicles (RITE)
Modelling and optimization of energy management systems for plug-in hybrid vehicles
AI-assisted real-time digital twin for electric drivetrains
EENE: Energy Effective Navigation for EVs