Dr Waqas Jamil
- wjamil at bournemouth dot ac dot uk
- Post Doctoral Research Assistant
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Biography
Waqas Jamil researches on algorithms, with a focus on algorithmic and game-theoretic learning. His work advances learning algorithms. Waqas has successfully bridged academia, industry, and research by teaching, consulting for financial firms on algorithmic solutions, and contributing to high-impact projects on machine learning. His work demonstrates both theoretical rigor and practical relevance. For more information, visit https://yjw.info.
Journal Articles
- Jamil, W. and Bouchachia, A., 2022. Iterative ridge regression using the aggregating algorithm. Pattern Recognition Letters, 158, 34-41.
- Jamil, W. and Bouchachia, A., 2021. Competitive Normalized Least-Squares Regression. IEEE Transactions on Neural Networks and Learning Systems, 32 (7), 3262-3267.
- Jamil, W. and Bouchachia, A., 2020. Online Bayesian shrinkage regression. Neural Computing and Applications.
- Jamil, W. and Bouchachia, A., 2020. Competitive regularised regression. Neurocomputing, 390, 374-383.
Conferences
- Jamil, W. and Bouchachia, A., 2019. Model selection in online learning for times series forecasting. Advances in Intelligent Systems and Computing, 840, 83-95.
- Jamil, W. and Bouchachia, A., 2019. Online Bayesian shrinkage regression. ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 431-436.
- Jamil, W., Duong, N.C., Wang, W., Mansouri, C., Mohamad, S. and Bouchachia, A., 2018. Scalable online learning for flink: SOLMA library. ACM International Conference Proceeding Series.
- Jamil, W., Kaliniskan, Y. and Bouchachia, H., 2017. Aggregation algorithm vs. Average for time series prediction. CEUR Workshop Proceedings, 2069.
Theses
- Jamil, W., 2020. Competitive regression. PhD Thesis. Bournemouth University, Faculty of Science and Technology.