Search Results for author: E. Veronica Belmega

Found 7 papers, 0 papers with code

A Game-Theoretic Approach for PMU Deployment Against False Data Injection Attacks

no code implementations16 Apr 2024 Sajjad Maleki, Subhash Lakshminarayana, E. Veronica Belmega, Carsten Maple

Phasor Measurement Units (PMUs) are used in the measurement, control and protection of power grids.

The Impact of Load Altering Attacks on Distribution Systems with ZIP Loads

no code implementations10 Nov 2023 Sajjad Maleki, Shijie Pan, E. Veronica Belmega, Charalambos Konstantinou, Subhash Lakshminarayana

Load-altering attacks (LAAs) pose a significant threat to power systems with Internet of Things (IoT)-controllable load devices.

RNN-Based GNSS Positioning using Satellite Measurement Features and Pseudorange Residuals

no code implementations8 Jun 2023 Ibrahim Sbeity, Christophe Villien, Benoît Denis, E. Veronica Belmega

In the Global Navigation Satellite System (GNSS) context, the growing number of available satellites has lead to many challenges when it comes to choosing the most accurate pseudorange contributions, given the strong impact of biased measurements on positioning accuracy, particularly in single-epoch scenarios.

Adaptive extra-gradient methods for min-max optimization and games

no code implementations ICLR 2021 Kimon Antonakopoulos, E. Veronica Belmega, Panayotis Mertikopoulos

We present a new family of min-max optimization algorithms that automatically exploit the geometry of the gradient data observed at earlier iterations to perform more informative extra-gradient steps in later ones.

Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach

no code implementations ICLR 2020 Kimon Antonakopoulos, E. Veronica Belmega, Panayotis Mertikopoulos

Motivated by applications to machine learning and imaging science, we study a class of online and stochastic optimization problems with loss functions that are not Lipschitz continuous; in particular, the loss functions encountered by the optimizer could exhibit gradient singularities or be singular themselves.

Stochastic Optimization

Online convex optimization and no-regret learning: Algorithms, guarantees and applications

no code implementations12 Apr 2018 E. Veronica Belmega, Panayotis Mertikopoulos, Romain Negrel, Luca Sanguinetti

Spurred by the enthusiasm surrounding the "Big Data" paradigm, the mathematical and algorithmic tools of online optimization have found widespread use in problems where the trade-off between data exploration and exploitation plays a predominant role.

Metric Learning

Distributed stochastic optimization via matrix exponential learning

no code implementations3 Jun 2016 Panayotis Mertikopoulos, E. Veronica Belmega, Romain Negrel, Luca Sanguinetti

In this paper, we investigate a distributed learning scheme for a broad class of stochastic optimization problems and games that arise in signal processing and wireless communications.

Stochastic Optimization valid

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