Uncertainty in Artificial Intelligence

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  • 2020

    PS3: Partition-based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data

    Fajri, R., Khoshrou, S., Peharz, R. & Pechenizkiy, M., 18 Sep 2020, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • Towards Robust Classification with Deep Generative Forests

    Correia, A. H. C., Peharz, R. & Campos, C. D., 11 Jul 2020, ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    10 Downloads (Pure)
  • 2019

    An experimental study of prior dependence in Bayesian network structure learning

    Correia, A. H. C., de Campos, C. P. & van der Gaag, L. C., 2019, Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications. De Bock, J., de Campos, C. P., de Cooman, G., Quaeghebeur, E. & Wheeler, G. (eds.). PMLR, p. 78-81 4 p. (Proceedings of Machine Learning Research; vol. 103).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
  • Automatic Bayesian Density Analysis

    Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K. & Valera, I., 2019, Proceedings of The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19). AAAI Press, p. 5207-5215 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
  • Bayesian Learning of Sum-Product Networks

    Trapp, M., Peharz, R., Ge, H., Pernkopf, F. & Ghahramani, Z., 26 May 2019, Advances in Neural Information Processing Systems (NeurIPS). Curran Associates, p. 6347-6358 (Advances in Neural Information Processing Systems; vol. 32).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • Faster attend-infer-repeat with tractable probabilistic models

    Stelzner, K., Peharz, R. & Kersting, K., 1 Jan 2019, 36th International Conference on Machine Learning, ICML 2019. Proceedings of Machine Learning Research, p. 10455-10466 12 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    2 Citations (Scopus)
  • Hierarchical decompositional mixtures of variational autoencoders

    Tan, P. L. & Peharz, R., 1 Jan 2019, 36th International Conference on Machine Learning, ICML 2019. Proceedings of Machine Learning Research, p. 10701-10711 11 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • Human-in-the-loop feature selection

    Correia, A. H. C. & Lecue, F., 23 Jul 2019, 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. Palo Alto: AAAI Press, p. 2438-2445 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
    1 Citation (Scopus)
  • Minimal random code learning: Getting bits back from compressed model parameters

    Havasi, M., Peharz, R. & Hernández-Lobato, J. M., 1 Jan 2019, International Conference on Learning Representations. 7 ed.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  • Random sum-product networks: A simple and effective approach to probabilistic deep learning

    Peharz, R., Vergari, A., Stelzner, K., Molina, A., Shao, X., Trapp, M., Kersting, K. & Ghahramani, Z., 2019, Conference on Uncertainty in Artificial Intelligence (UAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    7 Citations (Scopus)
  • Robustness in sum-product networks with continuous and categorical data

    de Wit, R. C., de Campos, C. P., Conaty, D. & Martínez del Rincon, J., 2019, Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications. De Bock, J., de Campos, C. P., de Cooman, G., Quaeghebeur, E. & Wheeler, G. (eds.). PMLR, p. 156-158 3 p. (Proceedings of Machine Learning Research; vol. 103).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
  • Towards scalable and robust sum-product networks

    Correia, A. H. C. & de Campos, C. P., 2019, Scalable Uncertainty Management - 13th International Conference, SUM 2019, Proceedings. Ben Amor, N., Quost, B. & Theobald, M. (eds.). Cham: Springer, p. 409-422 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11940 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Citation (Scopus)
    6 Downloads (Pure)
  • 2016

    Partial Data Querying Through Racing Algorithms

    Nguyen, V-L., Destercke, S. & Masson, M-H., 2016, Integrated Uncertainty in Knowledge Modelling and Decision Making 2016. Springer, p. 163-174

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Citation (Scopus)