Publications
2024
Model-Based Meta-Reinforcement Learning for Hyperparameter Optimization
J. Albrechts, H. Martin, M. Tavakol
International Conference on Intelligent Data Engineering and Automated Learning.
2023
Toward Robust Uncertainty Estimation with Random Activation Functions
Y. Stoyanova, S. Ghandi, M. Tavakol
Proceedings of the AAAI 2023, the Thirty-Seventh AAAI Conference on Artificial Intelligence.
FastDTI: Drug-Target Interaction Prediction using Multimodality and Transformers
M. Boezer, M. Tavakol, Z. Sajadi
Proceedings of the Northern Lights Deep Learning Workshop.
2022
Matrix factorization with denoising autoencoders for prediction of drug–target interactions
S.Z. Sajadi, M.A. Zare Chahooki, M. Tavakol, S. Gharaghani
Journal of Molecular Diversity, 1-11
Survey on Fair Reinforcement Learning: Theory and Practice
P. Gajane, A. Saxena, M. Tavakol, G. Fletcher, M. Pechenizkiy
arXiv preprint arXiv:2205.10032
MuseBar: Alleviating Posterior Collapse in Recurrent VAEs toward Music Generation
H. Wu and M. Tavakol
International Symposium on Intelligent Data Analysis, IDA 2022
2021
Rating Player Actions in Soccer
U. Dick, M. Tavakol, and U. Brefeld
Frontiers in Sports and Active Living, section Sports Science, Technology and Engineering, 2021
An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting
A. Saadallah, M. Tavakol, and K. Morik
International Conference on Data Engineering, ICDE 2021
2020
Fair Classification with Counterfactual Learning
M. Tavakol
International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020
[Slides]
Distantly Supervised Question Parsing
H. Zafar, M. Tavakol, and J. Lehmann
European Conference on Artificial Intelligence, ECAI 2020
[Code]
2019
HyperUCB: Hyperparameter Optimization using Contextual Bandits
M. Tavakol, S. Mair, and K. Morik
ECML Workshop on Automated Data Science, 2019
[Poster]
Contextual Models for Sequential Recommendation
M. Tavakol, PhD Dissertation, TU Darmstadt, 2019
Personalized Transaction Kernels for Recommmendation via MCTS
M. Tavakol, T. Joppen, U. Brefeld, and J. Fürnkranz
Proceedings of the German Conference on Artificial Intelligence (KI), 2019.
[Code] / [Slides]
2018
MDP-based Itinerary Recommendation using Geo-Tagged Social Media
R. Gaonkar, M. Tavakol, and U. Brefeld
Proceedings of the Seventeenth International Symposium on Intelligent Data Analysis, 2018
[Code] / [Slides] / [Poster]
2017
A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations
M. Tavakol and U. Brefeld
Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML 2017
[Code] / [Slides] / [Poster]
2016
A Preference-Based Bandit Framework for Personalized Recommendation
M. Tavakol and U. Brefeld
DA2PL Euro mini conference 2016
[Slides]
Feature Extraction and Aggregation for Predicting the Euro 2016
M. Tavakol, H. Zafartavanaelmi, U. Brefeld
Workshop of Sport Analysis, ECML 2016
[Slides]
2014
Factored MDPs for Detecting the Topic of User Sessions
M. Tavakol and U. Brefeld
Proceedings of the ACM Conference on Recommender Systems, 2014
[Code] / [Slides]
2012
A Distributed Q-Learning Approach for Variable Attention to Multiple Critics
M. Tavakol, M. N. Ahmadabadi, M. Mirian, M. Asadpour
International Conference on Neural Information Processing, ICONIP 2012