no code implementations • 25 Sep 2023 • Ioannis Kordonis, Emmanouil Theodosis, George Retsinas, Petros Maragos
Matrix Factorization (MF) has found numerous applications in Machine Learning and Data Mining, including collaborative filtering recommendation systems, dimensionality reduction, data visualization, and community detection.
no code implementations • 29 May 2023 • Emmanouil Theodosis, Karim Helwani, Demba Ba
Employing equivariance in neural networks leads to greater parameter efficiency and improved generalization performance through the encoding of domain knowledge in the architecture; however, the majority of existing approaches require an a priori specification of the desired symmetries.
1 code implementation • 16 Nov 2022 • Emmanouil Theodosis, Demba Ba
Deep neural networks lack straightforward ways to incorporate domain knowledge and are notoriously considered black boxes.
no code implementations • 13 Feb 2021 • Emmanouil Theodosis, Bahareh Tolooshams, Pranay Tankala, Abiy Tasissa, Demba Ba
Recent approaches in the theoretical analysis of model-based deep learning architectures have studied the convergence of gradient descent in shallow ReLU networks that arise from generative models whose hidden layers are sparse.
no code implementations • 16 Jun 2020 • Abiy Tasissa, Emmanouil Theodosis, Bahareh Tolooshams, Demba Ba
We propose a novel dense and sparse coding model that integrates both representation capability and discriminative features.
no code implementations • 9 Dec 2019 • Petros Maragos, Emmanouil Theodosis
Tropical Geometry and Mathematical Morphology share the same max-plus and min-plus semiring arithmetic and matrix algebra.
no code implementations • 1 Nov 2018 • Emmanouil Theodosis, Petros Maragos
Weighted Finite State Transducers (WFSTs) are versatile data structures that can model a great number of problems, ranging from Automatic Speech Recognition to DNA sequencing.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 1 Nov 2018 • Emmanouil Theodosis, Petros Maragos
In particular, the proposed algorithm tries to localise the attacker by adapting the leniency parameter based on estimates about the state of the solution space.