Répertoire des expertises

Kusner, Matt J.

Répertoire des expertises

Kusner, Matt J.

Répertoire des expertises

Publications par date

Article de revue (3) Communication de conférence (31) Livre Chapitre de livre Brevet Rapport Thèse Ensemble de données Ressource pédagogique Image Enregistrement audio Enregistrement vidéo Autre

Matthew Joseph Kusner (34)

2024 (3)
- Narasiah, H., Kitouni, O., Scorsoglio, A., Sturdza, B. K., Hatcher, S., Katcher, K., Khalesi, J., Garcia, D., & Kusner, M. J. (2024). Machine learning discovery of cost-efficient dry cooler designs for concentrated solar power plants. Scientific Reports, 14(1), 19086.
- Gopakumar, V., Pamela, S., Zanisi, L., Li, Z., Gray, A., Brennand, D., Bhatia, N., Stathopoulos, G., Kusner, M. J., Deisenroth, M. P., & Anandkumar, A. (2024). Plasma surrogate modelling using Fourier neural operators. Nuclear Fusion, 64(5), 056025 (36 pages).
- Tsai, K., Pfohl, S. R., Salaudeen, O., Chiou, N., Kusner, M. J., D'amour, A., Koyejo, S., & Gretton, A. (mai 2024). Proxy Methods for Domain Adaptation [Communication écrite]. 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Spain (29 pages). Publié dans Proceedings of Machine Learning Research.
2023 (3)
- Alabdulmohsin, I., Chiou, N., D'Amour, A., Gretton, A., Koyejo, S., Kusner, M. J., Pfohl, S. R., Salaudeen, O., Schrouff, J., & Tsai, K. (avril 2023). Adapting to latent subgroup shifts via concepts and proxies [Communication écrite]. 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), Palau de Congressos, Valencia, Spain. Publié dans Proceedings of Machine Learning Research, 206.
- Kaddour, J., Key, O., Nawrot, P., Minervini, P., & Kusner, M. J. (décembre 2023). No train no gain: revisiting efficient training algorithms for transformer-based language models [Communication écrite]. 37th Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA.
- Padh, K., Zeitler, J., Watson, D. S., Kusner, M. J., Silva, R., & Kilbertus, N. (avril 2023). Stochastic Causal Programming for Bounding Treatment Effects [Communication écrite]. 2nd Conference on Causal Learning and Reasoning (CCLR 2023), Tübingen, Germany (35 pages). Publié dans Proceedings of Machine Learning Research, 213.
2022 (4)
- Zhu, Y., Gultchin, L., Gretton, A., Kusner, M. J., & Silva, R. (août 2022). Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach [Communication écrite]. 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022), Eindhoven, The Netherlands. Publié dans Proceedings of Machine Learning Research, 180.
- Zantedeschi, V., Kaddour, J., Franceschi, L., Kusner, M. J., & Niculae, V. (avril 2022). DAG Learning on the Permutahedron [Affiche]. 10th International Conference on Learning Representations (ICLR 2023) (9 pages).
- Maus, N. T., Jones, H. T., Moore, J. S., Kusner, M. J., Bradshaw, J., & Gardner, J. R. (novembre 2022). Local Latent Space Bayesian Optimization over Structured Inputs [Communication écrite]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, Louisiana, USA (14 pages).
- Kaddour, J., Liu, L., Silva, R., & Kusner, M. J. (novembre 2022). When Do Flat Minima Optimizers Work? [Communication écrite]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, Louisiana (19 pages).
2021 (7)
- Kaddour, J., Zhu, Y., Liu, Q., Kusner, M. J., & Silva, R. (décembre 2021). Causal effect inference for structured treatments [Communication écrite]. 35th Annual Conference on Neural Information Processing Systems (NeurIPS 2021).
- Liu, Q., Kusner, M. J., & Blunsom, P. (juin 2021). Counterfactual Data Augmentation for Neural Machine Translation [Communication écrite]. Conference of the North-American-Chapter of the Association-for-Computational-Linguistics - Human Language Technologies (NAACL-HLT 2021).
- Zantedeschi, V., Kusner, M. J., & Niculae, V. (juillet 2021). Learning Binary Decision Trees by Argmin Differentiation [Communication écrite]. Non spécifié.
- Agrawal, N., Bell, J., Gascón, A., & Kusner, M. J. (novembre 2021). MPC-friendly commitments for publicly verifiable covert security [Communication écrite]. ACM SIGSAC Conference on Computer and Communications Security (CCS 2021).
- Gultchin, L., Watson, D. S., Kusner, M. J., & Silva, R. (juillet 2021). Operationalizing complex causes: a pragmatic view of mediation [Communication écrite]. 38th International Conference on Machine Learning (ICML 2021). Publié dans Proceedings of Machine Learning Research, 139.
- Mastouri, A., Zhu, Y., Gultchin, L., Korba, A., Silva, R., Kusner, M. J., Gretton, A., & Muandet, K. (juillet 2021). Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction [Communication écrite]. 38th International Conference on Machine Learning (ICML 2021). Publié dans Proceedings of Machine Learning Research, 139.
- Wang, H., Liu, Q., Yue, X., Lasenby, J., & Kusner, M. J. (octobre 2021). Unsupervised Point Cloud Pre-training via Occlusion Completion [Communication écrite]. 18th IEEE/CVF International Conference on Computer Vision (ICCV 2021), Montreal, Quebec, Canada.
2020 (4)
- Kilbertus, N., Kusner, M. J., & Silva, R. (décembre 2020). A class of algorithms for general instrumental variable models [Communication écrite]. 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada.
- Bradshaw, J., Paige, B., Kusner, M. J., Segler, M. H. S., & Hernández-Lobato, J. M. (décembre 2020). Barking up the right tree: an approach to search over molecule synthesis DAGs [Communication écrite]. 34th International Conference on Neural Information Processing Systems (NIPS 2020), Vancouver, British Columbia, Canada.
- Gultchin, L., Kusner, M. J., Kanade, V., & Silva, R. (août 2020). Differentiable causal backdoor discovery [Communication écrite]. 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020). Publié dans Proceedings of Machine Learning Research, 108.
- Kusner, M. J., & Loftus, J. R. (2020). The Long Road to Fairer Algorithms. Nature, 578(7793), 34-36.
2019 (5)
- Bradshaw, J., Kusner, M. J., Paige, B., Segler, M. H. S., & Hernández-Lobato, J. M. (mai 2019). A generative model for electron paths [Communication écrite]. 7th International Conference on Learning Representations (ICLR 2019), New Orleans, Louisiana, USA (19 pages).
- Bradshaw, J., Paige, B., Kusner, M. J., Segler, M. H. S., & Hernández-Lobato, J. M. (décembre 2019). A model to search for synthesizable molecules [Communication écrite]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada.
- Kusner, M. J., Russell, C., Loftus, J. R., & Silva, R. (juin 2019). Making Decisions that Reduce Discriminatory Impact [Communication écrite]. 36th International Conference on Machine Learning (ICML 2019), Long Beach, California, USA. Publié dans Proceedings of Machine Learning Research, 97.
- Agrawal, N., Shamsabadi, A. S., Kusner, M. J., & Gascón, A. (novembre 2019). QUOTIENT: two-party secure neural network training and prediction [Communication écrite]. ACM SIGSAC Conference on Computer and Communications Security (CCS 2019), London, United Kingdom.
- Kilbertus, N., Ball, P. J., Kusner, M. J., Weller, A., & Silva, R. (juillet 2019). The Sensitivity of Counterfactual Fairness to Unmeasured Confounding [Communication écrite]. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel. Publié dans Proceedings of Machine Learning Research, 115.
2018 (3)
- Kilbertus, N., Gascón, A., Kusner, M. J., Veale, M., Gummadi, K. P., & Weller, A. (juillet 2018). Blind justice: fairness with encrypted sensitive attributes [Communication écrite]. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden. Publié dans Proceedings of Machine Learning Research, 80.
- Janz, D., Westhuizen, J. , Paige, B., Kusner, M. J., & Hernández-Lobato, J. M. (juillet 2018). Learning a Generative Model for Validity in Complex Discrete Structures [Communication écrite]. 35th International Conference on Machine Learning (ICLR 2018), Stockholm, Sweden (12 pages).
- Sanyal, A., Kusner, M. J., Gascón, A., & Kanade, V. (juillet 2018). TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service [Communication écrite]. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden. Publié dans Proceedings of Machine Learning Research, 80.
2017 (3)
- Kusner, M. J., Loftus, J., Russell, C., & Silva, R. (décembre 2017). Counterfactual fairness [Communication écrite]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA.
- Kusner, M. J., Paige, B., & Hernández-Lobato, J. M. (août 2017). Grammar Variational Autoencoder [Communication écrite]. 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia. Publié dans Proceedings of Machine Learning Research, 70.
- Russell, C., Kusner, M. J., Loftus, J. R., & Silva, R. (décembre 2017). When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness [Communication écrite]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Red Hook, New York. USA.
2016 (1)
- Huang, G., Guo, C., Kusner, M. J., Sun, Y., Weinberger, K. Q., & Sha, F. (décembre 2016). Supervised word mover's distance [Communication écrite]. 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain.
2014 (1)
- Gardner, J. R., Kusner, M. J., Xu, Z., Weinberger, K. Q., & Cunningham, J. P. (juin 2014). Bayesian optimization with inequality constraints [Communication écrite]. 31st International Conference on Machine Learning (ICML 2014), Beijing, China. Publié dans Proceedings of Machine Learning Research, 32(2).

Répertoire des expertises

Kusner, Matt J.

Répertoire des expertises

Kusner, Matt J.

Vous êtes ici

Publications par date

Matthew Joseph Kusner (34)