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Kusner, Matt J.

Directory of Experts

Kusner, Matt J.

Directory of Experts

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Journal article (3) Conference paper (31) Book Book chapter Patent Report Thesis Dataset Teaching resource Image Audio recording Video recording Other

Matthew Joseph Kusner (34)

Journal articles (3)
- 2024
  - 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).
- 2020
  - Kusner, M. J., & Loftus, J. R. (2020). The Long Road to Fairer Algorithms. Nature, 578(7793), 34-36.
Conference papers (31)
- 2024
  - Tsai, K., Pfohl, S. R., Salaudeen, O., Chiou, N., Kusner, M. J., D'amour, A., Koyejo, S., & Gretton, A. (2024, May). Proxy Methods for Domain Adaptation [Paper]. 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Spain (29 pages). Published in Proceedings of Machine Learning Research.
- 2023
  - Alabdulmohsin, I., Chiou, N., D'Amour, A., Gretton, A., Koyejo, S., Kusner, M. J., Pfohl, S. R., Salaudeen, O., Schrouff, J., & Tsai, K. (2023, April). Adapting to latent subgroup shifts via concepts and proxies [Paper]. 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), Palau de Congressos, Valencia, Spain. Published in Proceedings of Machine Learning Research, 206.
  - Kaddour, J., Key, O., Nawrot, P., Minervini, P., & Kusner, M. J. (2023, December). No train no gain: revisiting efficient training algorithms for transformer-based language models [Paper]. 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. (2023, April). Stochastic Causal Programming for Bounding Treatment Effects [Paper]. 2nd Conference on Causal Learning and Reasoning (CCLR 2023), Tübingen, Germany (35 pages). Published in Proceedings of Machine Learning Research, 213.
- 2022
  - Zhu, Y., Gultchin, L., Gretton, A., Kusner, M. J., & Silva, R. (2022, August). Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach [Paper]. 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022), Eindhoven, The Netherlands. Published in Proceedings of Machine Learning Research, 180.
  - Zantedeschi, V., Kaddour, J., Franceschi, L., Kusner, M. J., & Niculae, V. (2022, April). DAG Learning on the Permutahedron [Poster]. 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. (2022, November). Local Latent Space Bayesian Optimization over Structured Inputs [Paper]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, Louisiana, USA (14 pages).
  - Kaddour, J., Liu, L., Silva, R., & Kusner, M. J. (2022, November). When Do Flat Minima Optimizers Work? [Paper]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, Louisiana (19 pages).
- 2021
  - Kaddour, J., Zhu, Y., Liu, Q., Kusner, M. J., & Silva, R. (2021, December). Causal effect inference for structured treatments [Paper]. 35th Annual Conference on Neural Information Processing Systems (NeurIPS 2021).
  - Liu, Q., Kusner, M. J., & Blunsom, P. (2021, June). Counterfactual Data Augmentation for Neural Machine Translation [Paper]. 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. (2021, July). Learning Binary Decision Trees by Argmin Differentiation [Paper]. Unspecified.
  - Agrawal, N., Bell, J., Gascón, A., & Kusner, M. J. (2021, November). MPC-friendly commitments for publicly verifiable covert security [Paper]. ACM SIGSAC Conference on Computer and Communications Security (CCS 2021).
  - Gultchin, L., Watson, D. S., Kusner, M. J., & Silva, R. (2021, July). Operationalizing complex causes: a pragmatic view of mediation [Paper]. 38th International Conference on Machine Learning (ICML 2021). Published in Proceedings of Machine Learning Research, 139.
  - Mastouri, A., Zhu, Y., Gultchin, L., Korba, A., Silva, R., Kusner, M. J., Gretton, A., & Muandet, K. (2021, July). Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction [Paper]. 38th International Conference on Machine Learning (ICML 2021). Published in Proceedings of Machine Learning Research, 139.
  - Wang, H., Liu, Q., Yue, X., Lasenby, J., & Kusner, M. J. (2021, October). Unsupervised Point Cloud Pre-training via Occlusion Completion [Paper]. 18th IEEE/CVF International Conference on Computer Vision (ICCV 2021), Montreal, Quebec, Canada.
- 2020
  - Kilbertus, N., Kusner, M. J., & Silva, R. (2020, December). A class of algorithms for general instrumental variable models [Paper]. 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. (2020, December). Barking up the right tree: an approach to search over molecule synthesis DAGs [Paper]. 34th International Conference on Neural Information Processing Systems (NIPS 2020), Vancouver, British Columbia, Canada.
  - Gultchin, L., Kusner, M. J., Kanade, V., & Silva, R. (2020, August). Differentiable causal backdoor discovery [Paper]. 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020). Published in Proceedings of Machine Learning Research, 108.
- 2019
  - Bradshaw, J., Kusner, M. J., Paige, B., Segler, M. H. S., & Hernández-Lobato, J. M. (2019, May). A generative model for electron paths [Paper]. 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. (2019, December). A model to search for synthesizable molecules [Paper]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada.
  - Kusner, M. J., Russell, C., Loftus, J. R., & Silva, R. (2019, June). Making Decisions that Reduce Discriminatory Impact [Paper]. 36th International Conference on Machine Learning (ICML 2019), Long Beach, California, USA. Published in Proceedings of Machine Learning Research, 97.
  - Agrawal, N., Shamsabadi, A. S., Kusner, M. J., & Gascón, A. (2019, November). QUOTIENT: two-party secure neural network training and prediction [Paper]. 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. (2019, July). The Sensitivity of Counterfactual Fairness to Unmeasured Confounding [Paper]. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel. Published in Proceedings of Machine Learning Research, 115.
- 2018
  - Kilbertus, N., Gascón, A., Kusner, M. J., Veale, M., Gummadi, K. P., & Weller, A. (2018, July). Blind justice: fairness with encrypted sensitive attributes [Paper]. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden. Published in Proceedings of Machine Learning Research, 80.
  - Janz, D., Westhuizen, J. , Paige, B., Kusner, M. J., & Hernández-Lobato, J. M. (2018, July). Learning a Generative Model for Validity in Complex Discrete Structures [Paper]. 35th International Conference on Machine Learning (ICLR 2018), Stockholm, Sweden (12 pages).
  - Sanyal, A., Kusner, M. J., Gascón, A., & Kanade, V. (2018, July). TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service [Paper]. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden. Published in Proceedings of Machine Learning Research, 80.
- 2017
  - Kusner, M. J., Loftus, J., Russell, C., & Silva, R. (2017, December). Counterfactual fairness [Paper]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA.
  - Kusner, M. J., Paige, B., & Hernández-Lobato, J. M. (2017, August). Grammar Variational Autoencoder [Paper]. 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia. Published in Proceedings of Machine Learning Research, 70.
  - Russell, C., Kusner, M. J., Loftus, J. R., & Silva, R. (2017, December). When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness [Paper]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Red Hook, New York. USA.
- 2016
  - Huang, G., Guo, C., Kusner, M. J., Sun, Y., Weinberger, K. Q., & Sha, F. (2016, December). Supervised word mover's distance [Paper]. 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain.
- 2014
  - Gardner, J. R., Kusner, M. J., Xu, Z., Weinberger, K. Q., & Cunningham, J. P. (2014, June). Bayesian optimization with inequality constraints [Paper]. 31st International Conference on Machine Learning (ICML 2014), Beijing, China. Published in Proceedings of Machine Learning Research, 32(2).

Directory of Experts

Kusner, Matt J.

Directory of Experts

Kusner, Matt J.

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Publications by type

Matthew Joseph Kusner (34)