Gintare Karolina Dziugaite

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	All	Since 2015
Citations	1015	1010
h-index	12	12
i10-index	12	12

380

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2015201620172018201920207 37 88 181 318 370

Co-authors

Daniel M. RoyUniversity of Toronto, Dept of Statistical Sciences; Computer ScienceVerified email at utstat.toronto.edu
Jonathan FrankleMassachusetts Institute of TechnologyVerified email at mit.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Michael CarbinMassachusetts Institute of TechnologyVerified email at csail.mit.edu
Jeffrey NegreaUniversity of TorontoVerified email at utstat.toronto.edu
Ashish KhistiAssoc. Professor, University of TorontoVerified email at comm.utoronto.ca
Mahdi HaghifamPh.D. Candidate, University of TorontoVerified email at mail.utoronto.ca
Wei Ji Ma / Whee Ky MaProfessor of Neuroscience and Psychology at New York UniversityVerified email at nyu.edu
Ronald van den BergAssociate professor, University of StockholmVerified email at psychology.su.se
Shan ShenPostdoctoral Associate, Baylor College of MedicineVerified email at bcm.edu
Waseem GharbiehAI Research Scientist, LG ElectronicsVerified email at lge.com
Marc-Etienne BrunetUniversity of TorontoVerified email at cs.toronto.edu
Elnaz BarshanUniversity of WaterlooVerified email at uwaterloo.ca
Kyle HsuStanford UniversityVerified email at stanford.edu
Alexandre LacosteResearch Scientist, Element AIVerified email at elementai.com
Chin-Wei HuangPhD Student at Mila (University of Montreal)Verified email at umontreal.ca
Aaron CourvilleUniversité de MontréalVerified email at umontreal.ca
Pascal VincentFacebook AI Research; U. Montreal (Professor, Computer Sc. & Op. Res.); MILA; CIFARVerified email at iro.umontreal.ca

Gintare Karolina Dziugaite

Research Scientist, Element AI

Verified email at elementai.com - Homepage

Deep Learning Generative Models Statistical Learning theory Neural Network Models for Matrices Generalization Theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Training generative neural networks via maximum mean discrepancy optimization GK Dziugaite, DM Roy, Z Ghahramani arXiv preprint arXiv:1505.03906, 2015	316	2015
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	237	2017
A study of the effect of jpg compression on adversarial images GK Dziugaite, Z Ghahramani, DM Roy arXiv preprint arXiv:1608.00853, 2016	158	2016
Neural network matrix factorization GK Dziugaite, DM Roy arXiv preprint arXiv:1511.06443, 2015	84*	2015
Data-dependent PAC-Bayes priors via differential privacy GK Dziugaite, DM Roy Advances in Neural Information Processing Systems, 8430-8441, 2018	45	2018
The lottery ticket hypothesis at scale J Frankle, GK Dziugaite, DM Roy, M Carbin arXiv preprint arXiv:1903.01611 8, 2019	41*	2019
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Data-dependent PAC-Bayes priors via differential privacy GK Dziugaite, DM Roy	28*	2018
Requiem for the max rule? WJ Ma, S Shen, G Dziugaite, R van den Berg Vision Research 116, 179-193, 2015	25	2015
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, 11015-11025, 2019	17	2019
Roy, and Michael Carbin. The lottery ticket hypothesis at scale J Frankle, GK Dziugaite, M Daniel arXiv preprint arXiv:1903.01611 2, 3, 2019	15	2019
Linear mode connectivity and the lottery ticket hypothesis J Frankle, GK Dziugaite, DM Roy, M Carbin arXiv preprint arXiv:1912.05671, 2019	13	2019
Stabilizing the lottery ticket hypothesis J Frankle, GK Dziugaite, DM Roy, M Carbin arXiv preprint arXiv:1903.01611, 2019	13	2019
Roy, and Michael Carbin. 2019. Stabilizing the lottery ticket hypothesis J Frankle, GK Dziugaite, M Daniel arXiv preprint arXiv:1903.01611, 0	8
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 arXiv preprint arXiv:2004.12983, 2020	4	2020
Revisiting Generalization for Deep Learning: PAC-Bayes, Flat Minima, and Generative Models GK Dziugaite University of Cambridge, 2020	3	2020
On the role of data in PAC-Bayes bounds GK Dziugaite, K Hsu, W Gharbieh, DM Roy arXiv preprint arXiv:2006.10929, 2020	3	2020
RelatIF: Identifying Explanatory Training Examples via Relative Influence E Barshan, ME Brunet, GK Dziugaite arXiv preprint arXiv:2003.11630, 2020	3	2020
Stochastic neural network with kronecker flow CW Huang, A Touati, P Vincent, GK Dziugaite, A Lacoste, A Courville International Conference on Artificial Intelligence and Statistics, 4184-4194, 2020	1	2020
In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors J Negrea, GK Dziugaite, DM Roy arXiv preprint arXiv:1912.04265, 2019	1	2019
On the Information Complexity of Proper Learners for VC Classes in the Realizable Case M Haghifam, GK Dziugaite, S Moran, DM Roy arXiv preprint arXiv:2011.02970, 2020		2020

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