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Probabilistic Learning Group Empirical Inference Conference Paper Don’t Throw it Away! The Utility of Unlabeled Data in Fair Decision Making Rateike, M., Majumdar, A., Mineeva, O., Gummadi, K. P., Valera, I. In FAccT ’22: 2022 ACM Conference on Fairness, Accountability, and Transparency, 1421-1433, ACM, New York, NY, 5th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2022), June 2022 (Published) DOI BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper On the Fairness of Causal Algorithmic Recourse von Kügelgen, J., Karimi, A., Bhatt, U., Valera, I., Weller, A., Schölkopf, B. Proceedings of the 36th AAAI Conference on Artificial Intelligence, 9:9584-9594, AAAI Press, Palo Alto, CA, Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), February 2022, *also at ICML 2021 Workshop Algorithmic Recourse and NeurIPS 2020 Workshop Algorithmic Fairness through the Lens of Causality and Interpretability (AFCI) (Published) arXiv DOI URL BibTeX
Probabilistic Learning Group Conference Paper VACA: Designing Variational Graph Autoencoders for Causal Queries Sanchez-Martin, P., Rateike, M., Valera, I. In Proceedings of the 36th AAAI Conference on Artificial Intelligence, 7:8159-8168, AAAI Press, Palo Alto, CA, Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), February 2022 (Published) DOI BibTeX
Empirical Inference Probabilistic Learning Group Book Chapter Towards Causal Algorithmic Recourse Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I. In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (Published) DOI BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Scaling Guarantees for Nearest Counterfactual Explanations Mohammadi, K., Karimi, A., Barthe, G., Valera, I. AIES ’21: Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 177-187, (Editors: Marion Fourcade, Benjamin Kuipers, Seth Lazar and Deirdre K. Mulligan), ACM, New York, NY, Fourth AAAI/ACM Conference on AI, Ethics, and Society (AIES 2021), May 2021 (Published) arXiv DOI BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Algorithmic Recourse: from Counterfactual Explanations to Interventions Karimi, A., Schölkopf, B., Valera, I. FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 353-362, (Editors: Madeleine Clare Elish and William Isaac and Richard S. Zemel), ACM, New York, NY, ACM Conference on Fairness, Accountability, and Transparency (FAccT 2021), March 2021 (Published) DOI URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Karimi*, A., von Kügelgen*, J., Schölkopf, B., Valera, I. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 265-277, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020, *equal contribution (Published) arXiv URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Relative gradient optimization of the Jacobian term in unsupervised deep learning Gresele, L., Fissore, G., Javaloy, A., Schölkopf, B., Hyvarinen, A. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 16567-16578, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Fair Decisions Despite Imperfect Predictions Kilbertus, N., Gomez Rodriguez, M., Schölkopf, B., Muandet, K., Valera, I. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:277-287, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Model-Agnostic Counterfactual Explanations for Consequential Decisions Karimi, A., Barthe, G., Balle, B., Valera, I. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:895-905, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) arXiv URL BibTeX
Empirical Inference Perceiving Systems Probabilistic Learning Group Conference Paper From Variational to Deterministic Autoencoders Ghosh*, P., Sajjadi*, M. S. M., Vergari, A., Black, M. J., Schölkopf, B. 8th International Conference on Learning Representations (ICLR) , April 2020, *equal contribution (Published) arXiv URL BibTeX
Probabilistic Learning Group Article General Latent Feature Models for Heterogeneous Datasets Valera, I., Pradier, M. F., Lomeli, M., Ghahramani, Z. Journal of Machine Learning Research, 21(100):1-49, 2020 (Published) URL BibTeX
Probabilistic Learning Group Article Handling incomplete heterogeneous data using VAEs Nazábal, A., Olmos, P. M., Ghahramani, Z., Valera, I. Pattern Recognition, 107:107501, 2020 (Published) DOI BibTeX
Probabilistic Learning Group Article Preliminary Results on Different Text Processing Tasks Using Encoder-Decoder Networks and the Causal Feature Extractor Javaloy, A. G. G. Applied Sciences, 10(17):5772, 2020 (Published) DOI BibTeX
Probabilistic Learning Group Article Text Normalization Using Encoder-Decoder Networks Based on the Causal Feature Extractor Javaloy, A. G. G. Applied Sciences, 10(13):4551, 2020 (Published) DOI BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper 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. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), 115:334-344, Proceedings of Machine Learning Research, (Editors: Adams, Ryan P. and Gogate, Vibhav), PMLR, July 2019 (Published) URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Automatic Bayesian Density Analysis Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-19), 33:01, 5207-5215, AAAI.org, AAAI-19, January 2019 (Published) arXiv DOI BibTeX
Empirical Inference Probabilistic Learning Group Article Fairness Constraints: A Flexible Approach for Fair Classification Zafar, M. B., Valera, I., Gomez-Rodriguez, M., Gummadi, K. P. Journal of Machine Learning Research, 20(75):1-42, 2019 (Published) URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Bayesian Nonparametric Hawkes Processes Kapoor, J., Vergari, A., Gomez Rodriguez, M., Valera, I. Bayesian Nonparametrics workshop at the 32nd Conference on Neural Information Processing Systems, December 2018 (Published) PDF URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Boosting Black Box Variational Inference Locatello*, F., Dresdner*, G., R., K., Valera, I., Rätsch, G. Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 3405-3415, (Editors: S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett), Curran Associates, Inc., 32nd Annual Conference on Neural Information Processing Systems, December 2018, *equal contribution (Published) arXiv URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Enhancing the Accuracy and Fairness of Human Decision Making Valera, I., Singla, A., Gomez Rodriguez, M. Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 1774-1783, (Editors: S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett), Curran Associates, Inc., 32nd Annual Conference on Neural Information Processing Systems, December 2018 (Published) arXiv URL BibTeX
Empirical Inference Probabilistic Learning Group Article Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation Ruiz, F. J. R., Valera, I., Svensson, L., Perez-Cruz, F. IEEE Transactions on Cognitive Communications and Networking, 4(2):177-191, June 2018 (Published) DOI BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Probabilistic Deep Learning using Random Sum-Product Networks Peharz, R., Vergari, A., Stelzner, K., Molina, A., Trapp, M., Kersting, K., Ghahramani, Z. 2018 (Submitted) arXiv BibTeX
Empirical Inference Probabilistic Learning Group Article Visualizing and understanding Sum-Product Networks Vergari, A., Di Mauro, N., Esposito, F. Machine Learning, 2018 (Published) DOI BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper From Parity to Preference-based Notions of Fairness in Classification Zafar, M. B., Valera, I., Gomez Rodriguez, M., Gummadi, K., Weller, A. Advances in Neural Information Processing Systems 30 (NIPS 2017), 229-239, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., 31st Annual Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper On the Reliability of Information and Trustworthiness of Web Sources in Wikipedia Tabibian, B., Farajtabar, M., Valera, I., Song, L., Schölkopf, B., Gomez Rodriguez, M. Wikipedia workshop at the 10th International AAAI Conference on Web and Social Media (ICWSM), May 2016 (Published) URL BibTeX