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ORCIDAnastasia Borovykh
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2020 – today
- 2024
[j4]Anastasia Borovykh, Nikolas Kantas, Panos Parpas
, Grigorios A. Pavliotis:
Stochastic Mirror Descent for Convex Optimization with Consensus Constraints. SIAM J. Appl. Dyn. Syst. 23(3): 2208-2241 (2024)- [c3]Anastasios Lepipas, Anastasia Borovykh, Soteris Demetriou:
Username Squatting on Online Social Networks: A Study on X. AsiaCCS 2024 - [c2]Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri:
Leave-one-out Distinguishability in Machine Learning. ICLR 2024 - [i15]Anastasios Lepipas, Anastasia Borovykh, Soteris Demetriou:
Username Squatting on Online Social Networks: A Study on X. CoRR abs/2401.09209 (2024) - [i14]Mohammad Mahdi Maheri, Sandra Deepthy Siby, Sina Abdollahi, Anastasia Borovykh, Hamed Haddadi:
P4: Towards private, personalized, and Peer-to-Peer learning. CoRR abs/2405.17697 (2024) - [i13]Xavier F. Cadet, Anastasia Borovykh, Mohammad Malekzadeh, Sara Ahmadi-Abhari, Hamed Haddadi:
Deep Unlearn: Benchmarking Machine Unlearning. CoRR abs/2410.01276 (2024) - 2023
- [i12]Anastasia Borovykh, Nikolas Kantas, Panos Parpas, Greg Pavliotis:
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds. CoRR abs/2302.00766 (2023) - [i11]Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri:
Leave-one-out Distinguishability in Machine Learning. CoRR abs/2309.17310 (2023) - [i10]Boyang Gu, Anastasia Borovykh:
On original and latent space connectivity in deep neural networks. CoRR abs/2311.06816 (2023) - 2022
- [j3]Remco van der Meer, Cornelis W. Oosterlee, Anastasia Borovykh:
Optimally weighted loss functions for solving PDEs with Neural Networks. J. Comput. Appl. Math. 405: 113887 (2022) - 2021
- [c1]Mohammad Malekzadeh, Anastasia Borovykh, Deniz Gündüz:
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs. CCS 2021: 825-844 - [i9]Mohammad Malekzadeh, Anastasia Borovykh, Deniz Gündüz:
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs can be Secretly Coded into the Entropy of Classifiers' Outputs. CoRR abs/2105.12049 (2021) - [i8]Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou:
Quantifying Information Leakage from Gradients. CoRR abs/2105.13929 (2021) - 2020
- [i7]Shuaiqiang Liu, Álvaro Leitao, Anastasia Borovykh, Cornelis W. Oosterlee:
On Calibration Neural Networks for extracting implied information from American options. CoRR abs/2001.11786 (2020) - [i6]Remco van der Meer, Cornelis W. Oosterlee, Anastasia Borovykh:
Optimally weighted loss functions for solving PDEs with Neural Networks. CoRR abs/2002.06269 (2020) - [i5]Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou:
Layer-wise Characterization of Latent Information Leakage in Federated Learning. CoRR abs/2010.08762 (2020)
2010 – 2019
- 2019
- [j2]Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté:
Generalization in fully-connected neural networks for time series forecasting. J. Comput. Sci. 36 (2019) - [i4]Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté:
Generalisation in fully-connected neural networks for time series forecasting. CoRR abs/1902.05312 (2019) - [i3]Shuaiqiang Liu, Anastasia Borovykh, Lech A. Grzelak, Cornelis W. Oosterlee:
A neural network-based framework for financial model calibration. CoRR abs/1904.10523 (2019) - [i2]Anastasia Borovykh:
Analytic expressions for the output evolution of a deep neural network. CoRR abs/1912.08526 (2019) - 2018
- [j1]Anastasia Borovykh, Andrea Pascucci, Cornelis W. Oosterlee:
Efficient Computation of Various Valuation Adjustments Under Local Lévy Models. SIAM J. Financial Math. 9(1): 251-273 (2018) - [i1]Anastasia Borovykh:
A Gaussian Process perspective on Convolutional Neural Networks. CoRR abs/1810.10798 (2018)
Coauthor Index
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last updated on 2024-11-11 22:25 CET by the dblp team
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