People
About me
I am a full Professor on Machine Learning at the Department of Computer Science of Saarland University (Saarbrücken, Germany), and Adjunct Faculty at MPI for Software Systems in Saarbrücken (Saarbrücken, Germany).
I am a fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS), where I am part of the Robust Machine Learning Program and of the Saarbrücken Artificial Intelligence & Machine learning (Sam) Unit.
Prior to this, I was an independent group leader at the MPI for Intelligent Systems in Tübingen (Germany) until the end of the year. I have held a German Humboldt Post-Doctoral Fellowship, and a “Minerva fast track” fellowship from the Max Planck Society. I obtained my PhD in 2014 and MSc degree in 2012 from the University Carlos III in Madrid (Spain), and worked as postdoctoral researcher at the MPI for Software Systems (Germany) and at the University of Cambridge (UK).
Publications
2022
Mitigating Modality Collapse in Multimodal VAEs via Impartial Optimization Inproceedings
In: ICML, 2022.
RotoGrad: Gradient Homogenization in Multitask Learning Inproceedings
In: International Conference on Learning Representations, 2022.
2021
Boosting heterogeneous VAEs via multi-objective optimization Workshop
2021.
Scaling Guarantees for Nearest Counterfactual Explanations Inproceedings
In: Fourcade, Marion; Kuipers, Benjamin; Lazar, Seth; Mulligan, Deirdre K. (Ed.): AIES '21: AAAI/ACM Conference on AI, Ethics, and Society, Virtual Event, USA, May 19-21, 2021, pp. 177–187, ACM, 2021.
Algorithmic Recourse: from Counterfactual Explanations to Interventions Inproceedings
In: Elish, Madeleine Clare; Isaac, William; Zemel, Richard S. (Ed.): FAccT '21: 2021 ACM Conference on Fairness, Accountability, and Transparency, Virtual Event / Toronto, Canada, March 3-10, 2021, pp. 353–362, ACM, 2021.
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries Journal Article
In: CoRR, vol. abs/2110.14690, 2021.
A Ranking Approach to Fair Classification Inproceedings
In: COMPASS '21: ACM SIGCAS Conference on Computing and Sustainable Societies, Virtual Event, Australia, 28 June 2021 - 2 July 2021, pp. 115–125, ACM, 2021.
Springer, vol. 12457, 2021, ISBN: 978-3-030-67657-5.
Springer, vol. 12458, 2021, ISBN: 978-3-030-67660-5.
Springer, vol. 12459, 2021, ISBN: 978-3-030-67663-6.
2020
Lipschitz standardization for robust multivariate learning Journal Article
In: CoRR, vol. abs/2002.11369, 2020.
Model-Agnostic Counterfactual Explanations for Consequential Decisions Inproceedings
In: Chiappa, Silvia; Calandra, Roberto (Ed.): The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], pp. 895–905, PMLR, 2020.
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Inproceedings
In: Larochelle, Hugo; Ranzato, Marc'Aurelio; Hadsell, Raia; Balcan, Maria-Florina; Lin, Hsuan-Tien (Ed.): Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
Algorithmic Recourse: from Counterfactual Explanations to Interventions Journal Article
In: CoRR, vol. abs/2002.06278, 2020.
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Journal Article
In: CoRR, vol. abs/2006.06831, 2020.
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Journal Article
In: CoRR, vol. abs/2010.04050, 2020.
Scaling Guarantees for Nearest Counterfactual Explanations Journal Article
In: CoRR, vol. abs/2010.04965, 2020.
On the Fairness of Causal Algorithmic Recourse Journal Article
In: CoRR, vol. abs/2010.06529, 2020.
General Latent Feature Models for Heterogeneous Datasets Journal Article
In: J. Mach. Learn. Res., vol. 21, pp. 100:1–100:49, 2020.
Handling incomplete heterogeneous data using VAEs Journal Article
In: Pattern Recognit., vol. 107, pp. 107501, 2020.
Fair Decisions Despite Imperfect Predictions Inproceedings
In: Chiappa, Silvia; Calandra, Roberto (Ed.): The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], pp. 277–287, PMLR, 2020.
2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions Journal Article
In: CoRR, vol. abs/1905.11190, 2019.
Fairness Constraints: A Flexible Approach for Fair Classification Journal Article
In: J. Mach. Learn. Res., vol. 20, pp. 75:1–75:42, 2019.
One-Network Adversarial Fairness Inproceedings
In: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, pp. 2412–2420, AAAI Press, 2019.
Automatic Bayesian Density Analysis Inproceedings
In: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, pp. 5207–5215, AAAI Press, 2019.
Improving Consequential Decision Making under Imperfect Predictions Journal Article
In: CoRR, vol. abs/1902.02979, 2019.
2018
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation Journal Article
In: IEEE Trans. Cogn. Commun. Netw., vol. 4, no. 2, pp. 177–191, 2018.
Enhancing the Accuracy and Fairness of Human Decision Making Inproceedings
In: Bengio, Samy; Wallach, Hanna M.; Larochelle, Hugo; Grauman, Kristen; Cesa-Bianchi, Nicolò; Garnett, Roman (Ed.): Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, pp. 1774–1783, 2018.
Boosting Black Box Variational Inference Inproceedings
In: Bengio, Samy; Wallach, Hanna M.; Larochelle, Hugo; Grauman, Kristen; Cesa-Bianchi, Nicolò; Garnett, Roman (Ed.): Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, pp. 3405–3415, 2018.
Enhancing the Accuracy and Fairness of Human Decision Making Journal Article
In: CoRR, vol. abs/1805.10318, 2018.
Handling Incomplete Heterogeneous Data using VAEs Journal Article
In: CoRR, vol. abs/1807.03653, 2018.
Automatic Bayesian Density Analysis Journal Article
In: CoRR, vol. abs/1807.09306, 2018.
2017
Fairness Constraints: Mechanisms for Fair Classification Inproceedings
In: Singh, Aarti; Zhu, Xiaojin (Jerry) (Ed.): Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA, pp. 962–970, PMLR, 2017.
Automatic Discovery of the Statistical Types of Variables in a Dataset Inproceedings
In: Precup, Doina; Teh, Yee Whye (Ed.): Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, pp. 3521–3529, PMLR, 2017.
From Parity to Preference-based Notions of Fairness in Classification Inproceedings
In: Guyon, Isabelle; Luxburg, Ulrike; Bengio, Samy; Wallach, Hanna M.; Fergus, Rob; Vishwanathan, S. V. N.; Garnett, Roman (Ed.): Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, pp. 229–239, 2017.
Uncovering the Dynamics of Crowdlearning and the Value of Knowledge Inproceedings
In: Rijke, Maarten; Shokouhi, Milad; Tomkins, Andrew; Zhang, Min (Ed.): Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, WSDM 2017, Cambridge, United Kingdom, February 6-10, 2017, pp. 61–70, ACM, 2017.
Distilling Information Reliability and Source Trustworthiness from Digital Traces Inproceedings
In: Barrett, Rick; Cummings, Rick; Agichtein, Eugene; Gabrilovich, Evgeniy (Ed.): Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017, pp. 847–855, ACM, 2017.
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Inproceedings
In: Barrett, Rick; Cummings, Rick; Agichtein, Eugene; Gabrilovich, Evgeniy (Ed.): Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017, pp. 1171–1180, ACM, 2017.
Modeling the Dynamics of Learning Activity on the Web Inproceedings
In: Barrett, Rick; Cummings, Rick; Agichtein, Eugene; Gabrilovich, Evgeniy (Ed.): Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017, pp. 1421–1430, ACM, 2017.
General Latent Feature Modeling for Data Exploration Tasks Journal Article
In: CoRR, vol. abs/1707.08352, 2017.
2016
Infinite Continuous Feature Model for Psychiatric Comorbidity Analysis Journal Article
In: Neural Comput., vol. 28, no. 2, pp. 354–381, 2016.
Infinite Factorial Unbounded-State Hidden Markov Model Journal Article
In: IEEE Trans. Pattern Anal. Mach. Intell., vol. 38, no. 9, pp. 1816–1828, 2016.
Learning and Forecasting Opinion Dynamics in Social Networks Inproceedings
In: Lee, Daniel D.; Sugiyama, Masashi; Luxburg, Ulrike; Guyon, Isabelle; Garnett, Roman (Ed.): Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pp. 397–405, 2016.
On the Efficiency of the Information Networks in Social Media Inproceedings
In: Bennett, Paul N.; Josifovski, Vanja; Neville, Jennifer; Radlinski, Filip (Ed.): Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA, February 22-25, 2016, pp. 83–92, ACM, 2016.
Modeling the Dynamics of Online Learning Activity Journal Article
In: CoRR, vol. abs/1610.05775, 2016.
Distilling Information Reliability and Source Trustworthiness from Digital Traces Journal Article
In: CoRR, vol. abs/1610.07472, 2016.
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Journal Article
In: CoRR, vol. abs/1610.08452, 2016.
Uncovering the Dynamics of Crowdlearning and the Value of Knowledge Journal Article
In: CoRR, vol. abs/1612.04831, 2016.
2015
A Bayesian nonparametric approach for blind multiuser channel estimation Inproceedings
In: 23rd European Signal Processing Conference, EUSIPCO 2015, Nice, France, August 31 - September 4, 2015, pp. 2766–2770, IEEE, 2015.
Modeling Adoption and Usage of Competing Products Inproceedings
In: Aggarwal, Charu C.; Zhou, Zhi-Hua; Tuzhilin, Alexander; Xiong, Hui; Wu, Xindong (Ed.): 2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, November 14-17, 2015, pp. 409–418, IEEE Computer Society, 2015.