Artificial Neural Network Approach for Land Cover Classification of Fused Hyperspectral and Lidar Data. - Paris Giampouras; Eleni Charou; Anastasios L. Kesidis (AIAI, 2013)

A variational Bayes algorithm for joint-sparse abundance estimation. - Paris V. Giampouras; Konstantinos E. Themelis; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (WHISPERS, 2014)

Online Bayesian low-rank subspace learning from partial observations. - Paris Giampouras; Athanasios A. Rontogiannis; Konstantinos E. Themelis; Konstantinos Koutroumbas (EUSIPCO, 2015)

Hyperspectral image unmixing via simultaneously sparse and low rank abundance matrix estimation. - Paris V. Giampouras; Konstantinos E. Themelis; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (WHISPERS, 2015)

Online low-rank subspace learning from incomplete data using rank revealing ℓ2/ℓ1 regularization. - Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (SSP, 2016)

Simultaneously Sparse and Low-Rank Abundance Matrix Estimation for Hyperspectral Image Unmixing. - Paris V. Giampouras; Konstantinos E. Themelis; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (IEEE Trans. Geosci. Remote. Sens., 2016)

Low-rank and sparse NMF for joint endmembers' number estimation and blind unmixing of hyperspectral images. - Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (EUSIPCO, 2017)

Alternating Iteratively Reweighted Minimization Algorithms for Low-Rank Matrix Factorization. - Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (CoRR, 2017)

Online sparse and low-rank subspace learning from incomplete data: A Bayesian view. - Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos E. Themelis; Konstantinos D. Koutroumbas (Signal Process., 2017)

Robust PCA via Alternating Iteratively Reweighted Low-Rank Matrix Factorization. - Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (ICIP, 2018)

A Computationally Efficient Tensor Completion Algorithm. - Ioannis C. Tsaknakis; Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (IEEE Signal Process. Lett., 2018)

A Projected Newton-type Algorithm for Nonnegative Matrix Factorization with Model Order Selection. - Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (ICASSP, 2019)

Alternating Iteratively Reweighted Least Squares Minimization for Low-Rank Matrix Factorization. - Paris V. Giampouras; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas (IEEE Trans. Signal Process., 2019)

A novel variational form of the Schatten-$p$ quasi-norm. - Paris Giampouras; René Vidal; Athanasios A. Rontogiannis; Benjamin D. Haeffele (NeurIPS, 2020)

Online Reweighted Least Squares Robust PCA. - Athanasios A. Rontogiannis; Paris V. Giampouras; Konstantinos D. Koutroumbas (IEEE Signal Process. Lett., 2020)

A Bayesian Approach to Block-Term Tensor Decomposition Model Selection and Computation. - Paris V. Giampouras; Athanasios A. Rontogiannis; Eleftherios Kofidis (EUSIPCO, 2021)

Rank-Revealing Block-Term Decomposition for Tensor Completion. - Athanasios A. Rontogiannis; Paris V. Giampouras; Eleftherios Kofidis (ICASSP, 2021)

Block-Term Tensor Decomposition: Model Selection and Computation. - Athanasios A. Rontogiannis; Eleftherios Kofidis; Paris V. Giampouras (IEEE J. Sel. Top. Signal Process., 2021)

A Projected Newton-type Algorithm for Rank - revealing Nonnegative Block - Term Tensor Decomposition. - Eleftherios Kofidis; Paris V. Giampouras; Athanasios A. Rontogiannis (EUSIPCO, 2022)

Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension. - Paris Giampouras; Benjamin David Haeffele; René Vidal (ICLR, 2022)

Reverse Engineering ℓp attacks: A block-sparse optimization approach with recovery guarantees. - Darshan Thaker; Paris Giampouras; René Vidal (ICML, 2022)

Block-Term Tensor Decomposition Model Selection and Computation: The Bayesian Way. - Paris V. Giampouras; Athanasios A. Rontogiannis; Eleftherios Kofidis (IEEE Trans. Signal Process., 2022)

Clustering-based Domain-Incremental Learning. - Christiaan Lamers; René Vidal; Nabil Belbachir; Niki van Stein; Thomas Bäck; Paris Giampouras (ICCV (Workshops), 2023)

The Ideal Continual Learner: An Agent That Never Forgets. - Liangzu Peng; Paris Giampouras; René Vidal (ICML, 2023)

A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions. - Darshan Thaker; Paris Giampouras; René Vidal (CoRR, 2023)

Online rank-revealing block-term tensor decomposition. - Athanasios A. Rontogiannis; Eleftherios Kofidis; Paris V. Giampouras (Signal Process., 2023)

Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery. - Paris Giampouras; HanQin Cai; René Vidal (CoRR, 2024)

Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework. - Terje Mildner; Oliver Hamelijnck; Paris Giampouras; Theodoros Damoulas (CoRR, 2025)

DES-LOC: Desynced Low Communication Adaptive Optimizers for Training Foundation Models. - Alex Iacob; Lorenzo Sani; Mher Safaryan; Paris Giampouras; Samuel Horváth; Andrej Jovanovic; Meghdad Kurmanji; Preslav Aleksandrov; William F. Shen; Xinchi Qiu; Nicholas D. Lane (CoRR, 2025)