Anastasia Borovykh

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 21

Top Topics

Gaussian Process

Sensitive Attributes

Top Venues

J. Comput. Sci.

SIAM J. Appl. Dyn. Syst.

Publications

Anastasios Lepipas, Anastasia Borovykh, Soteris Demetriou
Username Squatting on Online Social Networks: A Study on X. AsiaCCS (2024)
Mohammad Mahdi Maheri, Sandra Deepthy Siby, Sina Abdollahi, Anastasia Borovykh, Hamed Haddadi
P4: Towards private, personalized, and Peer-to-Peer learning. CoRR (2024)
Anastasios Lepipas, Anastasia Borovykh, Soteris Demetriou
Username Squatting on Online Social Networks: A Study on X. CoRR (2024)
Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri
Leave-one-out Distinguishability in Machine Learning. ICLR (2024)
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) (2024)
Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri
Leave-one-out Distinguishability in Machine Learning. CoRR (2023)
Anastasia Borovykh, Nikolas Kantas, Panos Parpas, Greg Pavliotis
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds. CoRR (2023)
Boyang Gu, Anastasia Borovykh
On original and latent space connectivity in deep neural networks. CoRR (2023)
Remco van der Meer, Cornelis W. Oosterlee, Anastasia Borovykh
Optimally weighted loss functions for solving PDEs with Neural Networks. J. Comput. Appl. Math. 405 (2022)
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 (2021)
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)
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou
Quantifying Information Leakage from Gradients. CoRR (2021)
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou
Layer-wise Characterization of Latent Information Leakage in Federated Learning. CoRR (2020)
Shuaiqiang Liu, Álvaro Leitao, Anastasia Borovykh, Cornelis W. Oosterlee
On Calibration Neural Networks for extracting implied information from American options. CoRR (2020)
Remco van der Meer, Cornelis W. Oosterlee, Anastasia Borovykh
Optimally weighted loss functions for solving PDEs with Neural Networks. CoRR (2020)
Anastasia Borovykh
Analytic expressions for the output evolution of a deep neural network. CoRR (2019)
Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté
Generalization in fully-connected neural networks for time series forecasting. J. Comput. Sci. 36 (2019)
Shuaiqiang Liu, Anastasia Borovykh, Lech A. Grzelak, Cornelis W. Oosterlee
A neural network-based framework for financial model calibration. CoRR (2019)
Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté
Generalisation in fully-connected neural networks for time series forecasting. CoRR (2019)
Anastasia Borovykh, Andrea Pascucci, Cornelis W. Oosterlee
Efficient Computation of Various Valuation Adjustments Under Local Lévy Models. SIAM J. Financial Math. 9 (1) (2018)
Anastasia Borovykh
A Gaussian Process perspective on Convolutional Neural Networks. CoRR (2018)