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Gintare Karolina Dziugaite
Gintare Karolina Dziugaite
Google DeepMind
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Año
Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data
GK Dziugaite, DM Roy
arXiv preprint arXiv:1703.11008, 2017
6692017
Training generative neural networks via maximum mean discrepancy optimization
GK Dziugaite, DM Roy, Z Ghahramani
arXiv preprint arXiv:1505.03906, 2015
6022015
A study of the effect of jpg compression on adversarial images
GK Dziugaite, Z Ghahramani, DM Roy
arXiv preprint arXiv:1608.00853, 2016
4892016
Linear mode connectivity and the lottery ticket hypothesis
J Frankle, GK Dziugaite, D Roy, M Carbin
International Conference on Machine Learning, 3259-3269, 2020
3632020
Stabilizing the lottery ticket hypothesis
J Frankle, GK Dziugaite, DM Roy, M Carbin
arXiv preprint arXiv:1903.01611, 2019
3222019
Deep learning on a data diet: Finding important examples early in training
M Paul, S Ganguli, GK Dziugaite
Advances in Neural Information Processing Systems 34, 20596-20607, 2021
1742021
Pruning neural networks at initialization: Why are we missing the mark?
J Frankle, GK Dziugaite, DM Roy, M Carbin
arXiv preprint arXiv:2009.08576, 2020
1672020
Neural network matrix factorization
GK Dziugaite, DM Roy
arXiv preprint arXiv:1511.06443, 2015
1562015
Information-theoretic generalization bounds for SGLD via data-dependent estimates
J Negrea, M Haghifam, GK Dziugaite, A Khisti, DM Roy
Advances in Neural Information Processing Systems 32, 2019
1242019
Data-dependent PAC-Bayes priors via differential privacy
GK Dziugaite, DM Roy
Advances in neural information processing systems 31, 2018
1242018
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the neural tangent kernel
S Fort, GK Dziugaite, M Paul, S Kharaghani, DM Roy, S Ganguli
Advances in Neural Information Processing Systems 33, 5850-5861, 2020
1172020
Sharpened generalization bounds based on conditional mutual information and an application to noisy, iterative algorithms
M Haghifam, J Negrea, A Khisti, DM Roy, GK Dziugaite
Advances in Neural Information Processing Systems 33, 9925-9935, 2020
962020
On the role of data in PAC-Bayes bounds
GK Dziugaite, K Hsu, W Gharbieh, G Arpino, D Roy
International Conference on Artificial Intelligence and Statistics, 604-612, 2021
842021
In search of robust measures of generalization
GK Dziugaite, A Drouin, B Neal, N Rajkumar, E Caballero, L Wang, ...
Advances in Neural Information Processing Systems 33, 11723-11733, 2020
782020
Relatif: Identifying explanatory training samples via relative influence
E Barshan, ME Brunet, GK Dziugaite
International Conference on Artificial Intelligence and Statistics, 1899-1909, 2020
672020
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Data-dependent PAC-Bayes priors via differential privacy
GK Dziugaite, DM Roy
66*2018
Information-theoretic generalization bounds for stochastic gradient descent
G Neu, GK Dziugaite, M Haghifam, DM Roy
Conference on Learning Theory, 3526-3545, 2021
582021
In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors
J Negrea, GK Dziugaite, D Roy
International Conference on Machine Learning, 7263-7272, 2020
522020
Neurips 2020 competition: Predicting generalization in deep learning
Y Jiang, P Foret, S Yak, DM Roy, H Mobahi, GK Dziugaite, S Bengio, ...
arXiv preprint arXiv:2012.07976, 2020
442020
Requiem for the max rule?
WJ Ma, S Shen, G Dziugaite, R van den Berg
Vision Research 116, 179-193, 2015
342015
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