H-BayesClust: A New Hierarchical Clustering Based on Bayesian Networks. - Morteza Haghir Chehreghani; Hassan Abolhassani (ADMA, 2007)

Mining Maximal Embedded Unordered Tree Patterns. - Mostafa Haghir Chehreghani; Masoud Rahgozar; Caro Lucas; Morteza Haghir Chehreghani (CIDM, 2007)

Clustering Rooted Ordered Trees. - Mostafa Haghir Chehreghani; Masoud Rahgozar; Caro Lucas; Morteza Haghir Chehreghani (CIDM, 2007)

Attaining Higher Quality for Density Based Algorithms. - Morteza Haghir Chehreghani; Hassan Abolhassani; Mostafa Haghir Chehreghani (RR, 2007)

A heuristic algorithm for clustering rooted ordered trees. - Mostafa Haghir Chehreghani; Masoud Rahgozar; Caro Lucas; Morteza Haghir Chehreghani (Intell. Data Anal., 2007)

Novel meta-heuristic algorithms for clustering web documents. - Mehrdad Mahdavi; Morteza Haghir Chehreghani; Hassan Abolhassani; Rana Forsati (Appl. Math. Comput., 2008)

Improving density-based methods for hierarchical clustering of web pages. - Morteza Haghir Chehreghani; Hassan Abolhassani; Mostafa Haghir Chehreghani (Data Knowl. Eng., 2008)

Density link-based methods for clustering web pages. - Morteza Haghir Chehreghani; Hassan Abolhassani; Mostafa Haghir Chehreghani (Decis. Support Syst., 2009)

Efficient rule based structural algorithms for classification of tree structured data. - Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani; Caro Lucas; Masoud Rahgozar; Euhanna Ghadimi (Intell. Data Anal., 2009)

The Minimum Transfer Cost Principle for Model-Order Selection. - Mario Frank 001; Morteza Haghir Chehreghani; Joachim M. Buhmann (ECML/PKDD (1), 2011)

OInduced: An Efficient Algorithm for Mining Induced Patterns From Rooted Ordered Trees. - Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani; Caro Lucas; Masoud Rahgozar (IEEE Trans. Syst. Man Cybern. Part A, 2011)

The information content in sorting algorithms. - Ludwig M. Busse; Morteza Haghir Chehreghani; Joachim M. Buhmann (ISIT, 2012)

Probabilistic Heuristics for Hierarchical Web Data Clustering. - Morteza Haghir Chehreghani; Mostafa Haghir Chehreghani; Hassan Abolhassani (Comput. Intell., 2012)

Information Theoretic Model Selection for Pattern Analysis. - Joachim M. Buhmann; Morteza Haghir Chehreghani; Mario Frank 001; Andreas P. Streich (ICML Unsupervised and Transfer Learning, 2012)

Information Theoretic Model Validation for Spectral Clustering. - Morteza Haghir Chehreghani; Alberto Giovanni Busetto; Joachim M. Buhmann (AISTATS, 2012)

Approximate Sorting. - Ludwig M. Busse; Morteza Haghir Chehreghani; Joachim M. Buhmann (GCPR, 2013)

Transactional Tree Mining. - Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani (ECML/PKDD (1), 2016)

K-Nearest Neighbor Search and Outlier Detection via Minimax Distances. - Morteza Haghir Chehreghani (SDM, 2016)

Modeling Transitivity in Complex Networks. - Morteza Haghir Chehreghani; Mostafa Haghir Chehreghani (UAI, 2016)

Adaptive trajectory analysis of replicator dynamics for data clustering. - Morteza Haghir Chehreghani (Mach. Learn., 2016)

Classification with Minimax Distance Measures. - Morteza Haghir Chehreghani (AAAI, 2017)

Feature-Oriented Analysis of User Profile Completion Problem. - Morteza Haghir Chehreghani (ECIR, 2017)

Clustering by Shift. - Morteza Haghir Chehreghani (ICDM, 2017)

Efficient Computation of Pairwise Minimax Distance Measures. - Morteza Haghir Chehreghani (ICDM, 2017)

Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. - Yuxin Chen 001; Jean-Michel Renders; Morteza Haghir Chehreghani; Andreas Krause 001 (UAI, 2017)

Efficient Context-Aware K-Nearest Neighbor Search. - Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani (ECIR, 2018)

Nonparametric Feature Extraction from Dendrograms. - Morteza Haghir Chehreghani; Mostafa Haghir Chehreghani (CoRR, 2018)

A Non-Convex Optimization Approach to Correlation Clustering. - Erik Thiel; Morteza Haghir Chehreghani; Devdatt P. Dubhashi (AAAI, 2019)

Lifelong Learning Starting from Zero. - Claes Strannegård; Herman Carlström; Niklas Engsner; Fredrik Mäkeläinen; Filip Slottner Seholm; Morteza Haghir Chehreghani (AGI, 2019)

Stochastic Incremental Algorithms for Optimal Transport with SON Regularizer. - Ashkan Panahi; Erik Thiel; Morteza Haghir Cheraghani; Devdatt P. Dubhashi (CoRR, 2019)

Nonparametric feature extraction based on Minimax distance. - Morteza Haghir Chehreghani (CoRR, 2019)

Spectral Analysis of Kernel and Neural Embeddings: Optimization and Generalization. - Emilio Jorge; Morteza Haghir Chehreghani; Devdatt P. Dubhashi (CoRR, 2019)

An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles. - Niklas Åkerblom; Yuxin Chen 001; Morteza Haghir Chehreghani (IJCAI, 2020)

Generation of Driving Scenario Trajectories with Generative Adversarial Networks. - Andreas Demetriou; Henrik Allsvåg; Sadegh Rahrovani; Morteza Haghir Chehreghani (ITSC, 2020)

Hierarchical Correlation Clustering and Tree Preserving Embedding. - Morteza Haghir Chehreghani (CoRR, 2020)

On the Unreasonable Effectiveness of Knowledge Distillation: Analysis in the Kernel Regime. - Arman Rahbar; Ashkan Panahi; Chiranjib Bhattacharyya; Devdatt P. Dubhashi; Morteza Haghir Chehreghani (CoRR, 2020)

Memory-Efficient Sampling for Minimax Distance Measures. - Fazeleh Sadat Hoseini; Morteza Haghir Chehreghani (CoRR, 2020)

Frank-Wolfe Optimization for Dominant Set Clustering. - Carl Johnell; Morteza Haghir Chehreghani (CoRR, 2020)

Model-Centric and Data-Centric Aspects of Active Learning for Neural Network Models. - John Daniel Bossér; Erik Sörstadius; Morteza Haghir Chehreghani (CoRR, 2020)

A Generic Framework for Clustering Vehicle Motion Trajectories. - Fazeleh Sadat Hoseini; Sadegh Rahrovani; Morteza Haghir Chehreghani (CoRR, 2020)

Unsupervised representation learning with Minimax distance measures. - Morteza Haghir Chehreghani (Mach. Learn., 2020)

Learning representations from dendrograms. - Morteza Haghir Chehreghani; Mostafa Haghir Chehreghani (Mach. Learn., 2020)

Accelerated proximal incremental algorithm schemes for non-strongly convex functions. - Ashkan Panahi; Morteza Haghir Chehreghani; Devdatt P. Dubhashi (Theor. Comput. Sci., 2020)

Model-Centric and Data-Centric Aspects of Active Learning for Deep Neural Networks. - John Daniel Bossér; Erik Sörstadius; Morteza Haghir Chehreghani (IEEE BigData, 2021)

Shallow Node Representation Learning using Centrality Indices. - Masoud Malek; Mostafa Haghir Chehreghani; Ehsan Nazerfard; Morteza Haghir Chehreghani (IEEE BigData, 2021)

Reliable Agglomerative Clustering. - Morteza Haghir Chehreghani (IJCNN, 2021)

Vehicle Motion Trajectories Clustering via Embedding Transitive Relations. - Fazeleh Sadat Hoseini; Sadegh Rahrovani; Morteza Haghir Chehreghani (ITSC, 2021)

Constrained Policy Gradient Method for Safe and Fast Reinforcement Learning: a Neural Tangent Kernel Based Approach. - Balázs Varga; Balázs Kulcsár; Morteza Haghir Chehreghani (CoRR, 2021)

Analysis of Driving Scenario Trajectories with Active Learning. - Sanna Jarl; Sadegh Rahrovani; Morteza Haghir Chehreghani (CoRR, 2021)

On Using Node Indices and Their Correlations for Fake Account Detection. - Sara Asghari; Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani (IEEE Big Data, 2022)

Graph Clustering Using Node Embeddings: An Empirical Study. - Mahdi Ghanbari; Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani (IEEE Big Data, 2022)

Autonomous Drug Design with Multi-Armed Bandits. - Hampus Gummesson Svensson; Esben Jannik Bjerrum; Christian Tyrchan; Ola Engkvist; Morteza Haghir Chehreghani (IEEE Big Data, 2022)

Efficient Optimization of Dominant Set Clustering with Frank-Wolfe Algorithms. - Carl Johnell; Morteza Haghir Chehreghani (CIKM, 2022)

Analysis of Knowledge Transfer in Kernel Regime. - Ashkan Panahi; Arman Rahbar; Chiranjib Bhattacharyya; Devdatt P. Dubhashi; Morteza Haghir Chehreghani (CIKM, 2022)

Trip Prediction by Leveraging Trip Histories from Neighboring Users. - Yuxin Chen 001; Morteza Haghir Chehreghani (ITSC, 2022)

Passive and Active Learning of Driver Behavior from Electric Vehicles. - Federica Comuni; Christopher Mészáros; Niklas Åkerblom; Morteza Haghir Chehreghani (ITSC, 2022)

Memory-Efficient Minimax Distance Measures. - Fazeleh Sadat Hoseini; Morteza Haghir Chehreghani (PAKDD (1), 2022)

TEP-GNN: Accurate Execution Time Prediction of Functional Tests Using Graph Neural Networks. - Hazem Peter Samoaa; Antonio Longa; Mazen Mohamad; Morteza Haghir Chehreghani; Philipp Leitner 001 (PROFES, 2022)

Deep Q-learning: a robust control approach. - Balázs Varga; Balázs Kulcsár; Morteza Haghir Chehreghani (CoRR, 2022)

An Online Learning Approach for Vehicle Usage Prediction During COVID-19. - Tobias Lindroth; Axel Svensson; Niklas Åkerblom; Mitra Pourabdollah; Morteza Haghir Chehreghani (CoRR, 2022)

Active learning of driving scenario trajectories. - Sanna Jarl; Linus Aronsson; Sadegh Rahrovani; Morteza Haghir Chehreghani (Eng. Appl. Artif. Intell., 2022)

A unified framework for online trip destination prediction. - Victor Eberstein; Jonas Sjöblom; Nikolce Murgovski; Morteza Haghir Chehreghani (Mach. Learn., 2022)

Non-uniform Sampling Methods for Large Itemset Mining. - Zahra Moteshaker Arani; Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani (IEEE Big Data, 2023)

Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes. - Simon Johansson; Ola Engkvist; Morteza Haghir Chehreghani; Alexander Schliep (IEEE Big Data, 2023)

Improved Tactical Decision Making and Control Architecture for Autonomous Truck in SUMO Using Reinforcement Learning. - Deepthi Pathare; Leo Laine; Morteza Haghir Chehreghani (IEEE Big Data, 2023)

Batch Mode Deep Active Learning for Regression on Graph Data. - Peter Samoaa; Linus Aronsson; Philipp Leitner 001; Morteza Haghir Chehreghani (IEEE Big Data, 2023)

Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework. - Arman Rahbar; Ashkan Panahi; Morteza Haghir Chehreghani; Devdatt P. Dubhashi; Hamid Krim (ICML, 2023)

Efficient Online Decision Tree Learning with Active Feature Acquisition. - Arman Rahbar; Ziyu Ye; Yuxin Chen 001; Morteza Haghir Chehreghani (IJCAI, 2023)

Active Learning with Positive and Negative Pairwise Feedback. - Linus Aronsson; Morteza Haghir Chehreghani (CoRR, 2023)

Prediction of Time and Distance of Trips Using Explainable Attention-based LSTMs. - Ebrahim Balouji; Jonas Sjöblom; Nikolce Murgovski; Morteza Haghir Chehreghani (CoRR, 2023)

A Unified Active Learning Framework for Annotating Graph Data with Application to Software Source Code Performance Prediction. - Peter Samoaa; Linus Aronsson; Antonio Longa; Philipp Leitner 001; Morteza Haghir Chehreghani (CoRR, 2023)

Combinatorial Gaussian Process Bandits in Bayesian Settings: Theory and Application for Energy-Efficient Navigation. - Jack Sandberg; Niklas Åkerblom; Morteza Haghir Chehreghani (CoRR, 2023)

A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles. - Niklas Åkerblom; Morteza Haghir Chehreghani (Trans. Mach. Learn. Res., 2023)

Online learning of network bottlenecks via minimax paths. - Niklas Åkerblom; Fazeleh Sadat Hoseini; Morteza Haghir Chehreghani (Mach. Learn., 2023)

Online learning of energy consumption for navigation of electric vehicles. - Niklas Åkerblom; Yuxin Chen 001; Morteza Haghir Chehreghani (Artif. Intell., 2023)

Do Kernel and Neural Embeddings Help in Training and Generalization? - Arman Rahbar; Emilio Jorge; Devdatt P. Dubhashi; Morteza Haghir Chehreghani (Neural Process. Lett., 2023)

A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories. - Andreas Demetriou; Henrik Alfsvåg; Sadegh Rahrovani; Morteza Haghir Chehreghani (SN Comput. Sci., 2023)

Shift of pairwise similarities for data clustering. - Morteza Haghir Chehreghani (Mach. Learn., 2023)

Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction. - Ali Samadzadeh; Fatemeh Sadat Tabatabaei Far; Ali Javadi; Ahmad Nickabadi; Morteza Haghir Chehreghani (Neural Process. Lett., 2023)

A Contextual Combinatorial Semi-Bandit Approach to Network Bottleneck Identification. - Fazeleh Sadat Hoseini; Niklas Åkerblom; Morteza Haghir Chehreghani (CIKM, 2024)

Hierarchical Correlation Clustering and Tree Preserving Embedding. - Morteza Haghir Chehreghani; Mostafa Haghir Chehreghani (CVPR, 2024)

Effective Acquisition Functions for Active Correlation Clustering. - Linus Aronsson; Morteza Haghir Chehreghani (CoRR, 2024)

Tactical Decision Making for Autonomous Trucks by Deep Reinforcement Learning with Total Cost of Operation Based Reward. - Deepthi Pathare; Leo Laine; Morteza Haghir Chehreghani (CoRR, 2024)

Less Is More - On the Importance of Sparsification for Transformers and Graph Neural Networks for TSP. - Attila Lischka; Jiaming Wu; Rafael Basso; Morteza Haghir Chehreghani; Balázs Kulcsár (CoRR, 2024)

Analysing the Behaviour of Tree-Based Neural Networks in Regression Tasks. - Peter Samoaa; Mehrdad Farahani; Antonio Longa; Philipp Leitner 001; Morteza Haghir Chehreghani (CoRR, 2024)

A GREAT Architecture for Edge-Based Graph Problems Like TSP. - Attila Lischka; Jiaming Wu; Morteza Haghir Chehreghani; Balázs Kulcsár (CoRR, 2024)

Diversity-Aware Reinforcement Learning for de novo Drug Design. - Hampus Gummesson Svensson; Christian Tyrchan; Ola Engkvist; Morteza Haghir Chehreghani (CoRR, 2024)

Sample-Efficient Curriculum Reinforcement Learning for Complex Reward Functions. - Kilian Freitag; Kristian Ceder; Rita Laezza; Knut Åkesson; Morteza Haghir Chehreghani (CoRR, 2024)

A unified active learning framework for annotating graph data for regression tasks. - Peter Samoaa; Linus Aronsson; Antonio Longa; Philipp Leitner 001; Morteza Haghir Chehreghani (Eng. Appl. Artif. Intell., 2024)

Correlation Clustering with Active Learning of Pairwise Similarities. - Linus Aronsson; Morteza Haghir Chehreghani (Trans. Mach. Learn. Res., 2024)

Tree Ensembles for Contextual Bandits. - Hannes Nilsson; Rikard Johansson; Niklas Åkerblom; Morteza Haghir Chehreghani (Trans. Mach. Learn. Res., 2024)

Utilizing reinforcement learning for de novo drug design. - Hampus Gummesson Svensson; Christian Tyrchan; Ola Engkvist; Morteza Haghir Chehreghani (Mach. Learn., 2024)

Online Learning Models for Vehicle Usage Prediction During COVID-19. - Tobias Lindroth; Axel Svensson; Niklas Åkerblom; Mitra Pourabdollah; Morteza Haghir Chehreghani (IEEE Trans. Intell. Transp. Syst., 2024)

Bayesian Analysis of Combinatorial Gaussian Process Bandits. - Jack Sandberg; Niklas Åkerblom; Morteza Haghir Chehreghani (ICLR, 2025)

Cost-Efficient Online Decision Making: A Combinatorial Multi-Armed Bandit Approach. - Arman Rahbar; Niklas Åkerblom; Morteza Haghir Chehreghani (Trans. Mach. Learn. Res., 2025)

Efficient Prior Selection in Gaussian Process Bandits with Thompson Sampling. - Jack Sandberg; Morteza Haghir Chehreghani (CoRR, 2025)

An Efficient Local Search Approach for Polarized Community Discovery in Signed Networks. - Linus Aronsson; Morteza Haghir Chehreghani (CoRR, 2025)

A Survey on Active Feature Acquisition Strategies. - Arman Rahbar; Linus Aronsson; Morteza Haghir Chehreghani (CoRR, 2025)

Mining transactional tree databases under homeomorphism. - Mostafa Haghir Chehreghani; Morteza Haghir Chehreghani (J. Supercomput., 2025)

A Benchmark Dataset for Graph Regression with Homogeneous and Multi-Relational Variants. - Peter Samoaa; Marcus Vukojevic; Morteza Haghir Chehreghani; Antonio Longa (CoRR, 2025)

Diverse Mini-Batch Selection in Reinforcement Learning for Efficient Chemical Exploration in de novo Drug Design. - Hampus Gummesson Svensson; Ola Engkvist; Jon Paul Janet; Christian Tyrchan; Morteza Haghir Chehreghani (CoRR, 2025)

Learning to Solve Multi-Objective Routing Problems on Multigraphs. - Filip Rydin; Attila Lischka; Jiaming Wu; Morteza Haghir Chehreghani; Balázs Kulcsár (CoRR, 2025)

Learning for routing: A guided review of recent developments and future directions. - Fangting Zhou; Attila Lischka; Balázs Kulcsár; Jiaming Wu; Morteza Haghir Chehreghani; Gilbert Laporte (CoRR, 2025)

AFABench: A Generic Framework for Benchmarking Active Feature Acquisition. - Valter Schütz; Han Wu; Reza Rezvan; Linus Aronsson; Morteza Haghir Chehreghani (CoRR, 2025)