2 citations · 2 across the 6 of their papers we have counts for
6 papers
AdaCubic: An Adaptive Cubic Regularization Optimizer for Deep Learning
Ioannis Tsingalis, Constantine Kotropoulos, Corentin Briat
A novel regularization technique, AdaCubic, is proposed that adapts the weight of the cubic term. The heart of AdaCubic is an auxiliary optimization problem with cubic constraints…
Quantized Rank Reduction: A Communications-Efficient Federated Learning Scheme for Network-Critical Applications
Dimitrios Kritsiolis, Constantine Kotropoulos
Federated learning is a machine learning approach that enables multiple devices (i.e., agents) to train a shared model cooperatively without exchanging raw data. This technique kee…
InterGridNet: An Electric Network Frequency Approach for Audio Source Location Classification Using Convolutional Neural Networks
Christos Korgialas, Ioannis Tsingalis, Georgios Tzolopoulos +1
A novel framework, called InterGridNet, is introduced, leveraging a shallow RawNet model for geolocation classification of Electric Network Frequency (ENF) signatures in the SP Cup…
Constructing and Analyzing Different Density Graphs for Path Extrapolation in Wikipedia
Martha Sotiroudi, Anastasia-Sotiria Toufa, Constantine Kotropoulos
Graph-based models have become pivotal in understanding and predicting navigational patterns within complex networks. Building on graph-based models, the paper advances path extrap…
Camera Model Identification Using Audio and Visual Content from Videos
Ioannis Tsingalis, Christos Korgialas, Constantine Kotropoulos
The identification of device brands and models plays a pivotal role in the realm of multimedia forensic applications. This paper presents a framework capable of identifying devices…
On Spectrogram Analysis in a Multiple Classifier Fusion Framework for Power Grid Classification Using Electric Network Frequency
Georgios Tzolopoulos, Christos Korgialas, Constantine Kotropoulos
The Electric Network Frequency (ENF) serves as a unique signature inherent to power distribution systems. Here, a novel approach for power grid classification is developed, leverag…