Morteza Haghir Chehreghani
Länk till akademisk webbplats: https://www.cse.chalmers.se/~haghir/
Visar 47 publikationer
Tree Ensembles for Contextual Bandits
Online Learning Models for Vehicle Usage Prediction During COVID-19
Online Learning of Energy Consumption for Navigation of Electric Vehicles
Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework
Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach
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
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
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
A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification
Efficient Optimization of Dominant Set Clustering with Frank-Wolfe Algorithms
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
Autonomous Drug Design with Multi-Armed Bandits
Analysis of Knowledge Transfer in Kernel Regime
Passive and Active Learning of Driver Behavior from Electric Vehicles
Active learning of driving scenario trajectories
TEP-GNN: Accurate Execution Time Prediction of Functional Tests Using Graph Neural Networks
Memory-Efficient Minimax Distance Measures
Controlling gene expression with deep generative design of regulatory DNA
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 9 forskningsprojekt
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
Real-Time Robust and AdaptIve Learning in ElecTric VEhicles (RITE)
Adaptiv neural styrning för framtida förnyelsebara bränslen
Modellering och optimering av energi-styrsystem för plugin hybridfordon
AI-assisterad realtids digital twin för elektriska drivlinor
EENE: Energieffektiv Navigering för Elfordon