Biorthogonal bases of compactly supported matrix valued wavelets. - Konstantinos Slavakis; Isao Yamada (ISSPA, 1999)

An efficient robust adaptive filtering scheme based on parallel subgradient projection techniques. - Isao Yamada; Konstantinos Slavakis; Kenyu Yamada (ICASSP, 2001)

Compactly supported matrix valued wavelets-biorthogonal unconditional bases. - Konstantinos Slavakis; Isao Yamada (ISCAS (2), 2001)

Spectrum estimation of real vector wide sense stationary processes by the Hybrid Steepest Descent Method. - Konstantinos Slavakis; Isao Yamada; Kohichi Sakaniwa (ICASSP, 2002)

An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques. - Isao Yamada; Konstantinos Slavakis; Kenyu Yamada (IEEE Trans. Signal Process., 2002)

Computation of symmetric positive definite Toeplitz matrices by the hybrid steepest descent method. - Konstantinos Slavakis; Isao Yamada; Kohichi Sakaniwa (Signal Process., 2003)

Robust Capon Beamforming by the Adaptive Projected Subgradient Method. - Konstantinos Slavakis; Masahiro Yukawa; Isao Yamada (ICASSP (4), 2006)

Adaptive projected subgradient method and its applications to robust signal processing. - Isao Yamada; Konstantinos Slavakis; Masahiro Yukawa; Renato L. G. Cavalcante (ISCAS, 2006)

A Bayesian Network Approach to Semantic Labelling of Text Formatting in XML Corpora of Documents. - Florendia Fourli-Kartsouni; Konstantinos Slavakis; Georgios Kouroupetroglou; Sergios Theodoridis (HCI (7), 2007)

Online Kernel-Based Classification by Projections. - Konstantinos Slavakis; Sergios Theodoridis; Isao Yamada (ICASSP (2), 2007)

Adaptive Parallel Quadratic-Metric Projection Algorithms. - Masahiro Yukawa; Konstantinos Slavakis; Isao Yamada (IEEE Trans. Speech Audio Process., 2007)

Robust Wideband Beamforming by the Hybrid Steepest Descent Method. - Konstantinos Slavakis; Isao Yamada (IEEE Trans. Signal Process., 2007)

Robust adaptive nonlinear beamforming by kernels and projection mappings. - Konstantinos Slavakis; Sergios Theodoridis; Isao Yamada (EUSIPCO, 2008)

Sliding window online Kernel-based classification by projection mappings. - Konstantinos Slavakis; Sergios Theodoridis (ISCAS, 2008)

Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings. - Konstantinos Slavakis; Sergios Theodoridis (EURASIP J. Adv. Signal Process., 2008)

Online Kernel-Based Classification Using Adaptive Projection Algorithms. - Konstantinos Slavakis; Sergios Theodoridis; Isao Yamada (IEEE Trans. Signal Process., 2008)

Affinely constrained online learning and its application to beamforming. - Konstantinos Slavakis; Sergios Theodoridis (ICASSP, 2009)

Signal processing in dual domain by adaptive projected subgradient method. - Masahiro Yukawa; Konstantinos Slavakis; Isao Yamada (DPS, 2009)

Adaptive constrained learning in reproducing Kernel Hilbert spaces: the robust beamforming case. - Konstantinos Slavakis; Sergios Theodoridis; Isao Yamada (IEEE Trans. Signal Process., 2009)

A novel adaptive algorithm for diffusion networks using projections onto hyperslabs. - Symeon Chouvardas; Konstantinos Slavakis; Sergios Theodoridis (CIP, 2010)

Adaptive algorithm for sparse system identification using projections onto weighted l1 balls. - Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis (ICASSP, 2010)

Multi-domain adaptive filtering by feasibility splitting. - Masahiro Yukawa; Konstantinos Slavakis; Isao Yamada (ICASSP, 2010)

Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces. - Pantelis Bouboulis; Sergios Theodoridis; Konstantinos Slavakis (ICPR, 2010)

Online Sparse System Identification and Signal Reconstruction using Projections onto Weighted ℓ1 Balls - Yannis Kopsinis; Konstantinos Slavakis; Sergios Theodoridis (CoRR, 2010)

Asymptotic minimization of sequences of loss functions constrained by families of quasi-nonexpansive mappings and its application to online learning - Konstantinos Slavakis; Isao Yamada (CoRR, 2010)

Multi-Domain Adaptive Learning Based on Feasibility Splitting and Adaptive Projected Subgradient Method. - Masahiro Yukawa; Konstantinos Slavakis; Isao Yamada (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2010)

Adaptive Kernel-Based Image Denoising Employing Semi-Parametric Regularization. - Pantelis Bouboulis; Konstantinos Slavakis; Sergios Theodoridis (IEEE Trans. Image Process., 2010)

Robust adaptive sparse system identification by using weighted l1 balls and Moreau envelopes. - Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis (EUSIPCO, 2011)

Trading off communications bandwidth with accuracy in adaptive diffusion networks. - Symeon Chouvardas; Konstantinos Slavakis; Sergios Theodoridis (ICASSP, 2011)

Revisiting adaptive least-squares estimation and application to online sparse signal recovery. - Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis (ICASSP, 2011)

Reduced complexity online sparse signal reconstruction using projections onto weighted ℓ1 balls. - Yannis Kopsinis; Konstantinos Slavakis; Sergios Theodoridis; Steve McLaughlin 001 (DSP, 2011)

Generalized Thresholding Sparsity-Aware Online Learning in a Union of Subspaces - Yannis Kopsinis; Konstantinos Slavakis; Sergios Theodoridis; Steve McLaughlin 001 (CoRR, 2011)

A Sparsity-Aware Adaptive Algorithm for Distributed Learning - Symeon Chouvardas; Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis (CoRR, 2011)

Adaptive Learning in a World of Projections. - Sergios Theodoridis; Konstantinos Slavakis; Isao Yamada (IEEE Signal Process. Mag., 2011)

Adaptive Robust Distributed Learning in Diffusion Sensor Networks. - Symeon Chouvardas; Konstantinos Slavakis; Sergios Theodoridis (IEEE Trans. Signal Process., 2011)

Online Sparse System Identification and Signal Reconstruction Using Projections Onto Weighted ell1 Balls. - Yannis Kopsinis; Konstantinos Slavakis; Sergios Theodoridis (IEEE Trans. Signal Process., 2011)

Sparsity-promoting adaptive algorithm for distributed learning in diffusion networks. - Symeon Chouvardas; Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis (EUSIPCO, 2012)

Generalized thresholding sparsity-aware algorithm for low complexity online learning. - Yannis Kopsinis; Konstantinos Slavakis; Sergios Theodoridis; Steve McLaughlin 001 (ICASSP, 2012)

Sparsity-Aware Learning and Compressed Sensing: An Overview - Sergios Theodoridis; Yannis Kopsinis; Konstantinos Slavakis (CoRR, 2012)

Adaptive Learning in Complex Reproducing Kernel Hilbert Spaces Employing Wirtinger's Subgradients. - Pantelis Bouboulis; Konstantinos Slavakis; Sergios Theodoridis (IEEE Trans. Neural Networks Learn. Syst., 2012)

Adaptive Multiregression in Reproducing Kernel Hilbert Spaces: The Multiaccess MIMO Channel Case. - Konstantinos Slavakis; Pantelis Bouboulis; Sergios Theodoridis (IEEE Trans. Neural Networks Learn. Syst., 2012)

A Sparsity Promoting Adaptive Algorithm for Distributed Learning. - Symeon Chouvardas; Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis (IEEE Trans. Signal Process., 2012)

Sparsity-Aware Adaptive Learning: A Set Theoretic Estimation Approach. - Sergios Theodoridis; Yannis Kopsinis; Konstantinos Slavakis; Symeon Chouvardas (ALCOSP, 2013)

Robust sparse embedding and reconstruction via dictionary learning. - Konstantinos Slavakis; Georgios B. Giannakis; Geert Leus (CISS, 2013)

New operators for fixed-point theory: The sparsity-aware learning case. - Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis (EUSIPCO, 2013)

Online robust portfolio risk management using total least-squares and parallel splitting algorithms. - Konstantinos Slavakis; Geert Leus; Georgios B. Giannakis (ICASSP, 2013)

Thresholding-based online algorithms of complexity comparable to sparse LMS methods. - Yannis Kopsinis; Konstantinos Slavakis; Sergios Theodoridis; Stephen McLaughlin 001 (ISCAS, 2013)

Generalized Iterative Thresholding for Sparsity-Aware Online Volterra System Identification. - Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis; Georgios B. Giannakis; Vassilis Kekatos (ISWCS, 2013)

Trading off Complexity With Communication Costs in Distributed Adaptive Learning via Krylov Subspaces for Dimensionality Reduction. - Symeon Chouvardas; Konstantinos Slavakis; Sergios Theodoridis (IEEE J. Sel. Top. Signal Process., 2013)

The Adaptive Projected Subgradient Method Constrained by Families of Quasi-nonexpansive Mappings and Its Application to Online Learning. - Konstantinos Slavakis; Isao Yamada (SIAM J. Optim., 2013)

Stochastic Analysis of Hyperslab-Based Adaptive Projected Subgradient Method Under Bounded Noise. - Symeon Chouvardas; Konstantinos Slavakis; Sergios Theodoridis; Isao Yamada (IEEE Signal Process. Lett., 2013)

Generalized Thresholding and Online Sparsity-Aware Learning in a Union of Subspaces. - Konstantinos Slavakis; Yannis Kopsinis; Sergios Theodoridis; Stephen McLaughlin 001 (IEEE Trans. Signal Process., 2013)

Big data clustering via random sketching and validation. - Panagiotis A. Traganitis; Konstantinos Slavakis; Georgios B. Giannakis (ACSSC, 2014)

Linear minimum mean-square error estimation based on high-dimensional data with missing values. - Mahdi Zamanighomi; Zhengdao Wang; Konstantinos Slavakis; Georgios B. Giannakis (CISS, 2014)

Clustering high-dimensional data via random sampling and consensus. - Panagiotis A. Traganitis; Konstantinos Slavakis; Georgios B. Giannakis (GlobalSIP, 2014)

Online dictionary learning from big data using accelerated stochastic approximation algorithms. - Konstantinos Slavakis; Georgios B. Giannakis (ICASSP, 2014)

Riemannian Multi-Manifold Modeling. - Xu Wang 066; Konstantinos Slavakis; Gilad Lerman (CoRR, 2014)

Modeling and Optimization for Big Data Analytics: (Statistical) learning tools for our era of data deluge. - Konstantinos Slavakis; Georgios B. Giannakis; Gonzalo Mateos (IEEE Signal Process. Mag., 2014)

Stochastic Approximation vis-a-vis Online Learning for Big Data Analytics [Lecture Notes]. - Konstantinos Slavakis; Seung-Jun Kim 002; Gonzalo Mateos; Georgios B. Giannakis (IEEE Signal Process. Mag., 2014)

Large-scale subspace clustering using random sketching and validation. - Panagiotis A. Traganitis; Konstantinos Slavakis; Georgios B. Giannakis (ACSSC, 2015)

Multi-Manifold Modeling in Non-Euclidean spaces. - Xu Wang 066; Konstantinos Slavakis; Gilad Lerman (AISTATS, 2015)

Spectral clustering of large-scale communities via random sketching and validation. - Panagiotis A. Traganitis; Konstantinos Slavakis; Georgios B. Giannakis (CISS, 2015)

Large-scale subspace clustering using sketching and validation. - Panagiotis A. Traganitis; Konstantinos Slavakis; Georgios B. Giannakis (CoRR, 2015)

Sketch and Validate for Big Data Clustering. - Panagiotis A. Traganitis; Konstantinos Slavakis; Georgios B. Giannakis (IEEE J. Sel. Top. Signal Process., 2015)

Clustering brain-network-connectivity states using kernel partial correlations. - Konstantinos Slavakis; Shiva Salsabilian; David S. Wack; Sarah Feldt Muldoon; Henry E. Baidoo-Williams; Jean M. Vettel; Matthew Cieslak; Scott T. Grafton (ACSSC, 2016)

Multi-kernel based nonlinear models for connectivity identification of brain networks. - G. V. Karanikolas; Georgios B. Giannakis; Konstantinos Slavakis; Richard M. Leahy (ICASSP, 2016)

Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding. - Ukash Nakarmi; Yihang Zhou; Jingyuan Lyu; Konstantinos Slavakis; Leslie Ying (ISBI, 2016)

Clustering time-varying connectivity networks by riemannian geometry: The brain-network case. - Konstantinos Slavakis; Shiva Salsabilian; David S. Wack; Sarah Feldt Muldoon (SSP, 2016)

Bi-Linear modeling of manifold-data geometry for Dynamic-MRI recovery. - Konstantinos Slavakis; Gaurav N. Shetty; Abhishek Bose; Ukash Nakarmi; Leslie Ying (CAMSAP, 2017)

Accelerating the hybrid steepest descent method for affinely constrained convex composite minimization tasks. - Konstantinos Slavakis; Isao Yamada; Shunsuke Ono (ICASSP, 2017)

M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging. - Ukash Nakarmi; Konstantinos Slavakis; Jingyuan Lyu; Leslie Ying (ISBI, 2017)

Riemannian-geometry-based modeling and clustering of network-wide non-stationary time series: The brain-network case. - Konstantinos Slavakis; Shiva Salsabilian; David S. Wack; Sarah Feldt Muldoon; Henry E. Baidoo-Williams; Jean M. Vettel; Matthew Cieslak; Scott T. Grafton (CoRR, 2017)

Stochastic Composite Convex Minimization with Affine Constraints. - Konstantinos Slavakis (ACSSC, 2018)

Fast Projection-Based Solvers for the Non-Convex Quadratically Constrained Feasibility Problem. - Konstantinos Slavakis; Aritra Konar; Nicholas D. Sidiropoulos (ICASSP, 2018)

MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging. - Ukash Nakarmi; Konstantinos Slavakis; Leslie Ying (ISBI, 2018)

Clustering Brain-Network Time Series by Riemannian Geometry. - Konstantinos Slavakis; Shiva Salsabilian; David S. Wack; Sarah Feldt Muldoon; Henry E. Baidoo-Williams; Jean M. Vettel; Matthew Cieslak; Scott T. Grafton (IEEE Trans. Signal Inf. Process. over Networks, 2018)

Brain-Network Clustering via Kernel-ARMA Modeling and the Grassmannian. - Cong Ye; Konstantinos Slavakis; Pratik V. Patil; Sarah Feldt Muldoon; John D. Medaglia (CoRR, 2019)

The Stochastic Fejér-Monotone Hybrid Steepest Descent Method and the Hierarchical RLS. - Konstantinos Slavakis (IEEE Trans. Signal Process., 2019)

Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case. - Gaurav N. Shetty; Konstantinos Slavakis; Ukash Nakarmi; Gesualdo Scutari; Leslie Ying (EUSIPCO, 2020)

Robust Hierarchical-Optimization RLS Against Sparse Outliers. - Konstantinos Slavakis; Sinjini Banerjee (IEEE Signal Process. Lett., 2020)

Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. - Gaurav N. Shetty; Konstantinos Slavakis; Abhishek Bose; Ukash Nakarmi; Gesualdo Scutari; Leslie Ying (IEEE Trans. Medical Imaging, 2020)

Outlier-Robust Kernel Hierarchical-Optimization RLS on a Budget with Affine Constraints. - Konstantinos Slavakis; Masahiro Yukawa (ICASSP, 2021)

Online Classification of Dynamic Multilayer-Network Time Series in Riemannian Manifolds. - Cong Ye; Konstantinos Slavakis; Johan Nakuci; Sarah Feldt Muldoon; John D. Medaglia (ICASSP, 2021)

Network clustering via kernel-ARMA modeling and the Grassmannian: The brain-network case. - Cong Ye; Konstantinos Slavakis; Pratik V. Patil; Johan Nakuci; Sarah Feldt Muldoon; John D. Medaglia (Signal Process., 2021)

online and lightweight kernel-based approximated policy iteration for dynamic p-norm linear adaptive filtering. - Yuki Akiyama; Minh Vu; Konstantinos Slavakis (CoRR, 2022)

Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case. - Konstantinos Slavakis; Gaurav N. Shetty; Loris Cannelli; Gesualdo Scutari; Ukash Nakarmi; Leslie Ying (IEEE Trans. Computational Imaging, 2022)

Kernel Regression Imputation in Manifolds: Videos of dMRI data. - Konstantinos Slavakis; Gaurav N. Shetty (IEEE DataPort, 2022)

Dynamic Selection of p-norm in Linear Adaptive Filtering via online Kernel-based Reinforcement Learning. - Minh Vu; Yuki Akiyama; Konstantinos Slavakis (ICASSP, 2023)

Multi-Linear Kernel Regression and Imputation in Data Manifolds. - Duc Thien Nguyen; Konstantinos Slavakis (CoRR, 2023)

Proximal Bellman Mappings for Reinforcement Learning and Their Application to Robust Adaptive Filtering. - Yuki Akiyama; Konstantinos Slavakis (ICASSP, 2024)

Multi-Linear Kernel Regression and Imputation VIA Manifold Learning: the Dynamic MRI Case. - Duc Thien Nguyen; Konstantinos Slavakis (ICASSP, 2024)

Multilinear Kernel Regression and Imputation via Manifold Learning. - Duc Thien Nguyen; Konstantinos Slavakis (CoRR, 2024)

Gaussian-Mixture-Model Q-Functions for Reinforcement Learning by Riemannian Optimization. - Minh Vu; Konstantinos Slavakis (CoRR, 2024)

Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering. - Yuki Akiyama; Minh Vu; Konstantinos Slavakis (IEEE Trans. Signal Process., 2024)

Imputation of time-varying edge flows in graphs by multilinear kernel regression and manifold learning. - Duc Thien Nguyen; Konstantinos Slavakis; Dimitris Pados (Signal Process., 2025)

Model-Free Adversarial Purification via Coarse-To-Fine Tensor Network Representation. - Guang Lin 002; Duc Thien Nguyen; Zerui Tao; Konstantinos Slavakis; Toshihisa Tanaka 001; Qibin Zhao (CoRR, 2025)

Nonparametric Bellman Mappings for Value Iteration in Distributed Reinforcement Learning. - Yuki Akiyama; Konstantinos Slavakis (CoRR, 2025)

Robust Invariant Representation Learning by Distribution Extrapolation. - Kotaro Yoshida; Konstantinos Slavakis (CoRR, 2025)