Tosca Lechner

According to our database, Tosca Lechner authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Score Design for Multi-Criteria Incentivization.

Anmol Kabra, Mina Karzand, Tosca Lechner, Nati Srebro, Serena Lutong Wang

Proceedings of the 5th Symposium on Foundations of Responsible Computing, 2024

Inherent limitations of dimensions for characterizing learnability of distribution classes.

Tosca Lechner, Shai Ben-David

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

On the Computability of Robust PAC Learning.

Pascale Gourdeau, Tosca Lechner, Ruth Urner

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Impossibility of Characterizing Distribution Learning - a simple solution to a long-standing problem.

Tosca Lechner, Shai Ben-David

CoRR, 2023

Adversarially Robust Learning with Uncertain Perturbation Sets.

Tosca Lechner, Vinayak Pathak, Ruth Urner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distribution Learnability and Robustness.

Shai Ben-David, Alex Bie, Gautam Kamath, Tosca Lechner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Strategic Classification with Unknown User Manipulations.

Tosca Lechner, Ruth Urner, Shai Ben-David

Proceedings of the International Conference on Machine Learning, 2023

2022

Inherent Limitations of Multi-Task Fair Representations.

Tosca Lechner, Shai Ben-David

Proceedings of the Conference on Lifelong Learning Agents, 2022

Learning Losses for Strategic Classification.

Tosca Lechner, Ruth Urner

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Impossibility results for fair representations.

Tosca Lechner, Shai Ben-David, Sushant Agarwal, Nivasini Ananthakrishnan

CoRR, 2021

Identifying regions of trusted predictions.

Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Open Problem: Are all VC-classes CPAC learnable?

Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner

Proceedings of the Conference on Learning Theory, 2021

Classification Confidence Scores with Point-wise Guarantees.

Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner

Proceedings of the Workshop on Artificial Intelligence Safety 2021 (SafeAI 2021) co-located with the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), 2021

2020

On Learnability wih Computable Learners.

Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner

Proceedings of the Algorithmic Learning Theory, 2020