Gintare Karolina Dziugaite
Affiliations:- Google Research
According to our database1,
Gintare Karolina Dziugaite
authored at least 41 papers
between 2015 and 2024.
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Bibliography
2024
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization.
CoRR, 2024
2023
The Cost of Down-Scaling Language Models: Fact Recall Deteriorates before In-Context Learning.
CoRR, 2023
CoRR, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023
2022
Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the IEEE International Symposium on Information Theory, 2022
2021
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
On the Information Complexity of Proper Learners for VC Classes in the Realizable Case.
CoRR, 2020
Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability.
CoRR, 2020
CoRR, 2020
Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning.
Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020
Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Revisiting generalization for deep learning: PAC-Bayes, flat minima, and generative models.
PhD thesis, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors.
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Data-dependent PAC-Bayes priors via differential privacy.
CoRR, 2017
Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017
2016
2015
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015