Morteza Haghir Chehreghani
Biträdande professor i artificiell intelligens (AI) och maskininlärning. PI för Machine Learning and Decision Making Lab.
Visar 60 publikationer
A Survey on Active Feature Acquisition Strategies
Bayesian Analysis of Combinatorial Gaussian Process Bandits
Modelling and optimization of energy management systems for plug-in hybrid vehicles
Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach
Learning for routing: A guided review of recent developments and future directions
Neural Approaches for Multi-Objective Routing on Multigraphs
Mining transactional tree databases under homeomorphism
Proceedings of the 15th International Conference on Shock and Impact Loads on Structures
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
Tree Ensembles for Contextual Bandits
Correlation Clustering with Active Learning of Pairwise Similarities
Utilizing reinforcement learning for de novo drug design
Hierarchical Correlation Clustering and Tree Preserving Embedding
Online Learning Models for Vehicle Usage Prediction During COVID-19
Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction
Deep Q-learning: a robust control approach
Do Kernel and Neural Embeddings Help in Training and Generalization?
Online Learning of Energy Consumption for Navigation of Electric Vehicles
Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories
Online Learning of Network Bottlenecks via Minimax Paths
De novo generated combinatorial library design
Efficient Online Decision Tree Learning with Active Feature Acquisition
Prediction of Time and Distance of Trips Using Explainable Attention-based LSTMs
Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes
Batch Mode Deep Active Learning for Regression on Graph Data
Shift of pairwise similarities for data clustering
A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles
Non-uniform Sampling Methods for Large Itemset Mining
Passive and Active Learning of Driver Behavior from Electric Vehicles
A unified framework for online trip destination prediction
On Using Node Indices and Their Correlations for Fake Account Detection
Active learning of driving scenario trajectories
Efficient Optimization of Dominant Set Clustering with Frank-Wolfe Algorithms
Autonomous Drug Design with Multi-Armed Bandits
Analysis of Knowledge Transfer in Kernel Regime
Graph Clustering Using Node Embeddings: An Empirical Study
TEP-GNN: Accurate Execution Time Prediction of Functional Tests Using Graph Neural Networks
Controlling gene expression with deep generative design of regulatory DNA
Memory-Efficient Minimax Distance Measures
Trip Prediction by Leveraging Trip Histories from Neighboring Users
Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction
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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Visar 12 forskningsprojekt
Cooperative Calibration for Enhanced Localization Services in Transport
Onsite Array Calibration for Joint Localization and Communication Systems
Digital Twin for Energy Prediction
ADMOL: Ett generellt ramverk för aktivt beslutsfattande i online-lärande
LEAR: Robust LEArning methods for electric vehicle Route selection
Energy-efficient autopilot (EcoPilot)
Energy-based models for supervised deep neural networks and their applications
Adaptiv neural styrning för framtida förnyelsebara bränslen
Real-Time Robust and AdaptIve Learning in ElecTric VEhicles (RITE)
Modellering och optimering av energi-styrsystem för plugin hybridfordon
AI-assisterad realtids digital twin för elektriska drivlinor
EENE: Energieffektiv Navigering för Elfordon