Recent publications
Article
Jose, ST & Moothedath, S 2024, 'Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis', Entropy, vol. 26, no. 7, 606. https://doi.org/10.3390/e26070606
Zhang, Y, Simeone, O, Jose, ST, Maggi, L & Valcarce, A 2023, 'Bayesian and Multi-Armed Contextual Meta-Optimization for Efficient Wireless Radio Resource Management', IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 5, pp. 1282-1295. https://doi.org/10.1109/TCCN.2023.3287240
Jose, ST & Simeone, O 2022, 'An information-theoretic analysis of the cost of decentralization for learning and inference under privacy constraints', Entropy, vol. 24, no. 4, 485. https://doi.org/10.3390/e24040485
Jose, ST & Simeone, O 2022, 'Error-Mitigation-Aided Optimization of Parameterized Quantum Circuits: Convergence Analysis', IEEE Transactions on Quantum Engineering, vol. 3, 3103119. https://doi.org/10.1109/TQE.2022.3229747
Jose, ST, Simeone, O & Durisi, G 2022, 'Transfer meta-learning: information- theoretic bounds and information meta-risk minimization', IEEE Transactions on Information Theory, vol. 68, no. 1, pp. 474-501. https://doi.org/10.1109/TIT.2021.3119605
Jose, ST & Simeone, O 2021, 'Free energy minimization: a unified framework for modeling, inference, learning, and optimization [lecture notes]', IEEE Signal Processing Magazine, vol. 38, no. 2, pp. 120-125. https://doi.org/10.1109/MSP.2020.3041414
Jose, ST & Simeone, O 2021, 'Information-theoretic generalization bounds for meta-learning and applications', Entropy, vol. 23, no. 1, 126. https://doi.org/10.3390/e23010126
Jose, ST & Kulkarni, AA 2020, 'Shannon Meets von Neumann: A Minimax Theorem for Channel Coding in the Presence of a Jammer', IEEE Transactions on Information Theory. https://doi.org/10.1109/TIT.2020.2971682
Conference contribution
Jose, S, Park, S & Simeone, O 2022, Information-theoretic analysis of epistemic uncertainty in Bayesian meta-learning. in G Camps-Valls, FJR Ruiz & I Valera (eds), International Conference on Artificial Intelligence and Statistics, 28-30 March 2022, A Virtual Conference. Proceedings of Machine Learning Research, vol. 151, Proceedings of Machine Learning Research, pp. 9758-9775, The 25th International Conference on Artificial Intelligence and Statistics, 28/03/22. <https://proceedings.mlr.press/v151/theresa-jose22a.html>
Jose, S & Simeone, O 2021, An information-theoretic analysis of the impact of task similarity on meta-learning. in 2021 IEEE International Symposium on Information Theory (ISIT)., 9517767, IEEE International Symposium on Information Theory proceedings, IEEE, pp. 1534-1539, 2021 IEEE International Symposium on Information Theory, Melbourne, Victoria, Australia, 12/07/21. https://doi.org/10.1109/ISIT45174.2021.9517767
Jose, S & Simeone, O 2021, A unified PAC-Bayesian framework for machine unlearning via information risk minimization. in 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)., 9596170, Machine learning for signal processing , IEEE. https://doi.org/10.1109/MLSP52302.2021.9596170
Rezazadeh, A, Jose, S, Durisi, G & Simeone, O 2021, Conditional mutual information-based generalization bound for meta learning. in 2021 IEEE International Symposium on Information Theory (ISIT)., 9518020, IEEE International Symposium on Information Theory proceedings, IEEE, pp. 1176-1181. https://doi.org/10.1109/ISIT45174.2021.9518020
Jose, S & Simeone, O 2021, Information-theoretic bounds on transfer generalization gap based on Jensen-Shannon divergence. in 2021 29th European Signal Processing Conference (EUSIPCO)., 9616270, European Signal Processing Conference , IEEE, pp. 1461-1465, 29th European Signal Processing Conference (EUSIPCO 2021), Dublin, Ireland, 23/08/21. https://doi.org/10.23919/EUSIPCO54536.2021.9616270
Jose, S, Simeone, O & Zhang, Y 2021, Transfer Bayesian meta-learning via weighted free energy minimization. in 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)., 9596239, Proceedings of the IEEE Signal Processing Society Workshop, IEEE, 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), Gold Coast, Queensland, Australia, 20/09/21. https://doi.org/10.1109/MLSP52302.2021.9596239
Jose, S & Simeone, O 2020, Address-event variable-length compression for time-encoded data. in IEEE International Symposium on Information Theory and Applications. <https://ieeexplore.ieee.org/document/9366190>
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