Anastasia Borovykh

According to our database, Anastasia Borovykh authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Stochastic Mirror Descent for Convex Optimization with Consensus Constraints.

Anastasia Borovykh, Nikolas Kantas, Panos Parpas, Grigorios A. Pavliotis

SIAM J. Appl. Dyn. Syst., 2024

Deep Unlearn: Benchmarking Machine Unlearning.

Xavier F. Cadet, Anastasia Borovykh, Mohammad Malekzadeh, Sara Ahmadi-Abhari, Hamed Haddadi

CoRR, 2024

P4: Towards private, personalized, and Peer-to-Peer learning.

Mohammad Mahdi Maheri, Sandra Deepthy Siby, Sina Abdollahi, Anastasia Borovykh, Hamed Haddadi

CoRR, 2024

Leave-one-out Distinguishability in Machine Learning.

Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Username Squatting on Online Social Networks: A Study on X.

Anastasios Lepipas, Anastasia Borovykh, Soteris Demetriou

Proceedings of the 19th ACM Asia Conference on Computer and Communications Security, 2024

2023

On original and latent space connectivity in deep neural networks.

Boyang Gu, Anastasia Borovykh

CoRR, 2023

Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds.

Anastasia Borovykh, Nikolas Kantas, Panos Parpas, Greg Pavliotis

CoRR, 2023

2022

Optimally weighted loss functions for solving PDEs with Neural Networks.

Remco van der Meer, Cornelis W. Oosterlee, Anastasia Borovykh

J. Comput. Appl. Math., 2022

2021

Quantifying Information Leakage from Gradients.

Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

CoRR, 2021

Honest-but-Curious Nets: Sensitive Attributes of Private Inputs can be Secretly Coded into the Entropy of Classifiers' Outputs.

Mohammad Malekzadeh, Anastasia Borovykh, Deniz Gündüz

CoRR, 2021

Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs.

Mohammad Malekzadeh, Anastasia Borovykh, Deniz Gündüz

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020

Layer-wise Characterization of Latent Information Leakage in Federated Learning.

Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

CoRR, 2020

On Calibration Neural Networks for extracting implied information from American options.

Shuaiqiang Liu, Álvaro Leitao, Anastasia Borovykh, Cornelis W. Oosterlee

CoRR, 2020

2019

Generalization in fully-connected neural networks for time series forecasting.

Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté

J. Comput. Sci., 2019

Analytic expressions for the output evolution of a deep neural network.

Anastasia Borovykh

CoRR, 2019

A neural network-based framework for financial model calibration.

Shuaiqiang Liu, Anastasia Borovykh, Lech A. Grzelak, Cornelis W. Oosterlee

CoRR, 2019

Generalisation in fully-connected neural networks for time series forecasting.

Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté

CoRR, 2019

2018

Efficient Computation of Various Valuation Adjustments Under Local Lévy Models.

Anastasia Borovykh, Andrea Pascucci, Cornelis W. Oosterlee

SIAM J. Financial Math., 2018

A Gaussian Process perspective on Convolutional Neural Networks.

Anastasia Borovykh

CoRR, 2018