Tanaka, M. (forthcoming). "Calibrated Quasi-Bayesian Uncertainty Quantification for Rank Aggregation", Proceedings of the 2026 13th International Conference on Soft Computing and Machine Intelligence (ISCMI 2026), IEEE.
Tanaka, M. (2026). "Variational Causal Learning for Dynamic Treatment Effects in Time Series Data with an Application to Wholesale Electricity Markets", Proceedings of the 2026 IEEE 4th Conference on Information Technology and Data Science (CITDS 2026), pp. 393-398, IEEE. Link
Tanaka, M. (2026). "Delayed Acceptance Markov Chain Monte Carlo for Robust Bayesian Analysis", In: Ferreira, D., von Rosen, D., Limnios, N., Ferreira, S. (eds) Mathematics for Industrial Applications. ICoMS 2025. Springer Proceedings in Mathematics & Statistics, vol 537, Springer. Link
Tanaka, M. (2025). "Modified Delayed Acceptance MCMC for Quasi-Bayesian Inference with Linear Moment Conditions", Proceedings of the 15th International Conference on Mathematics, Actuarial Science, Computer Science, and Statistics (MACS 2025), IEEE. Link
Tanaka, M. (2025). "Estimating Bidirectional Causal Effects with Large Scale Online Kernel Learning", Proceedings of the 2025 International Conference on Data Science and Intelligent Systems (DSIS 2025), Article 65, pp. 449-455, IEEE. Link
Tanaka, M. (2025). "Generalized Posterior Calibration via Sequential Monte Carlo Sampler", Proceedings of the 2024 6th Asia Conference on Machine Learning and Computing (ACMLC 2024), pp. 62-68, ACM. Excellent Oral Presentation. Link
Tanaka, M. (2024). "Weighted Particle-Based Optimization for Efficient Generalized Posterior Calibration", Proceedings of the 7th International Conference on Data Science and Its Applications 2024 (ICoDSA 2024), pp. 515-521, IEEE. Best Paper Award. Link
Tanaka, M. (2024). "Parameterizations for Gradient-based Markov Chain Monte Carlo on the Stiefel Manifold: A Comparative Study", Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning (CACML 2024), pp. 397-402, ACM. Link