Publications

Konstantinos Kalais and Sotirios Chatzis, “Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning,” Proc. International Conference on Machine Learning (ICML), July 2022. (Long Presentation; Acceptance Rate=2%)
Anastastios Antoniadis, Konstantinos P. Panousis, and Sotirios Chatzis, “Competing Mutual Information Constraints with Stochastic Competition-based Activations for Learning Diversified Representations,” Proc. AAAI Conference on Artificial Intelligence, Feb. 2022
Andreas Voskou, Konstantinos Panousis, Dimitrios Kosmopoulos, Dimitris Metaxas, and Sotirios Chatzis, “Stochastic Transformer Networks with Linear Competing Units: Application to end-to-end SL Translation,” Proc. International IEEE Conference on Computer Vision (ICCV), Oct. 2021.
Konstantinos Panousis, Antonis Alexos, Sergios Theodoridis, and Sotirios Chatzis, “Local Competition and Stochasticity for Adversarial Robustness in Deep Learning,” Proc. 24th International Conference on Artificial Intelligence and Statistics (AISTATS), April 2021.
Konstantinos Panousis*, Sotirios Chatzis*, and Sergios Theodoridis, "Nonparametric Bayesian Local Winner-Takes-All Networks," Proc. International Conference on Machine Learning (ICML), June 2019.

Lei Cheng, Feng Yin, Sergios Theodoridis, Sotirios Chatzis, and Tsung-Hui Chang, “Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling,” IEEE Signal Processing Magazine, vol. 39, no. 6, pp. 18-52, 2022.
Anastasios Petropoulos, Vasilios Siakoulis, Panagiotis Lazaris, and Sotirios Chatzis, “Re- constructing the interbank links using machine learning techniques. An application to the Greek Interbank Market,” Intelligent Systems with Applications, vol. 12, 2021.
Pavlos Nikolaidis and Sotirios Chatzis, “Gaussian Process-Based Bayesian Optimization for Data-Driven Unit Commitment,” International Journal of Electrical Power and Energy Systems, vol. 130, 2021.
Ioannis Stylios, Spyros Kokolakis, Olga Thanou, and Sotirios Chatzis, “Behavioral Biometrics & Continuous User Authentication on Mobile Devices: A Survey,” Information Fusion, vol. 66, pp. 76-99, 2021.
Sotirios P. Chatzis, Vasilis Siakoulis, Anastasios Petropoulos, Vangelis Stavroulakis, and Nikos Vlachogiannakis, “Forecasting stock market crisis events using deep and statistical machine learning techniques,” Expert Systems with Applications, vol. 112, pp. 353-371, Dec. 2018.