Konstantinos Slavakis

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 40

Top Topics

Adaptive Filtering

Steepest Descent Method

Kernel Regression

Reinforcement Learning

Top Venues

Publications

Yuki Akiyama, Konstantinos Slavakis
Proximal Bellman Mappings for Reinforcement Learning and Their Application to Robust Adaptive Filtering. ICASSP (2024)
Yuki Akiyama, Minh Vu, Konstantinos Slavakis
Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering. CoRR (2024)
Duc Thien Nguyen, Konstantinos Slavakis
Multilinear Kernel Regression and Imputation via Manifold Learning. CoRR (2024)
Duc Thien Nguyen, Konstantinos Slavakis
Multi-Linear Kernel Regression and Imputation VIA Manifold Learning: the Dynamic MRI Case. ICASSP (2024)
Yuki Akiyama, Konstantinos Slavakis
Proximal Bellman mappings for reinforcement learning and their application to robust adaptive filtering. CoRR (2023)
Duc Thien Nguyen, Konstantinos Slavakis
Multi-Linear Kernel Regression and Imputation in Data Manifolds. CoRR (2023)
Minh Vu, Yuki Akiyama, Konstantinos Slavakis
Dynamic Selection of p-norm in Linear Adaptive Filtering via online Kernel-based Reinforcement Learning. ICASSP (2023)
Yuki Akiyama, Minh Vu, Konstantinos Slavakis
online and lightweight kernel-based approximated policy iteration for dynamic p-norm linear adaptive filtering. CoRR (2022)
Konstantinos Slavakis, Gaurav N. Shetty, Loris Cannelli, Gesualdo Scutari, Ukash Nakarmi, Leslie Ying
Kernel Regression Imputation in Manifolds Via Bi-Linear Modeling: The Dynamic-MRI Case. IEEE Trans. Computational Imaging 8 (2022)
Minh Vu, Yuki Akiyama, Konstantinos Slavakis
Dynamic selection of p-norm in linear adaptive filtering via online kernel-based reinforcement learning. CoRR (2022)
Konstantinos Slavakis, Masahiro Yukawa
Outlier-Robust Kernel Hierarchical-Optimization RLS on a Budget with Affine Constraints. ICASSP (2021)
Cong Ye, Konstantinos Slavakis, Johan Nakuci, Sarah Feldt Muldoon, John D. Medaglia
Online Classification of Dynamic Multilayer-Network Time Series in Riemannian Manifolds. ICASSP (2021)
Cong Ye, Konstantinos Slavakis, Pratik V. Patil, Johan Nakuci, Sarah Feldt Muldoon, John D. Medaglia
Network clustering via kernel-ARMA modeling and the Grassmannian: The brain-network case. Signal Process. 179 (2021)
Gaurav N. Shetty, Konstantinos Slavakis, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying
Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case. EUSIPCO (2020)
Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. IEEE Trans. Medical Imaging 39 (3) (2020)
Cong Ye, Konstantinos Slavakis, Pratik V. Patil, Johan Nakuci, Sarah Feldt Muldoon, John D. Medaglia
Network Clustering Via Kernel-ARMA Modeling and the Grassmannian The Brain-Network Case. CoRR (2020)
Konstantinos Slavakis, Sinjini Banerjee
Robust Hierarchical-Optimization RLS Against Sparse Outliers. IEEE Signal Process. Lett. 27 (2020)
Gaurav N. Shetty, Konstantinos Slavakis, Ukash Nakarmi, Gesualdo Scutari, Leslie Ying
Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case. CoRR (2020)
Konstantinos Slavakis
The Stochastic Fejér-Monotone Hybrid Steepest Descent Method and the Hierarchical RLS. IEEE Trans. Signal Process. 67 (11) (2019)
Konstantinos Slavakis, Sinjini Banerjee
Robust Hierarchical-Optimization RLS Against Sparse Outliers. CoRR (2019)
Cong Ye, Konstantinos Slavakis, Pratik V. Patil, Sarah Feldt Muldoon, John D. Medaglia
Brain-Network Clustering via Kernel-ARMA Modeling and the Grassmannian. CoRR (2019)
Ukash Nakarmi, Konstantinos Slavakis, Leslie Ying
MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging. ISBI (2018)
Konstantinos Slavakis, Aritra Konar, Nicholas D. Sidiropoulos
Fast Projection-Based Solvers for the Non-Convex Quadratically Constrained Feasibility Problem. ICASSP (2018)
Konstantinos Slavakis, Shiva Salsabilian, David S. Wack, Sarah Feldt Muldoon, Henry E. Baidoo-Williams, Jean M. Vettel, Matthew Cieslak, Scott T. Grafton
Clustering Brain-Network Time Series by Riemannian Geometry. IEEE Trans. Signal Inf. Process. over Networks 4 (3) (2018)
Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Leslie Ying, Gesualdo Scutari
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. CoRR (2018)
Konstantinos Slavakis
Stochastic Composite Convex Minimization with Affine Constraints. ACSSC (2018)
Konstantinos Slavakis, Isao Yamada, Shunsuke Ono
Accelerating the hybrid steepest descent method for affinely constrained convex composite minimization tasks. ICASSP (2017)
Konstantinos Slavakis, Gaurav N. Shetty, Abhishek Bose, Ukash Nakarmi, Leslie Ying
Bi-Linear modeling of manifold-data geometry for Dynamic-MRI recovery. CAMSAP (2017)
Ukash Nakarmi, Konstantinos Slavakis, Jingyuan Lyu, Leslie Ying
M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging. ISBI (2017)
Konstantinos Slavakis, Shiva Salsabilian, David S. Wack, Sarah Feldt Muldoon, Henry E. Baidoo-Williams, Jean M. Vettel, Matthew Cieslak, Scott T. Grafton
Riemannian-geometry-based modeling and clustering of network-wide non-stationary time series: The brain-network case. CoRR (2017)
G. V. Karanikolas, Georgios B. Giannakis, Konstantinos Slavakis, Richard M. Leahy
Multi-kernel based nonlinear models for connectivity identification of brain networks. ICASSP (2016)
Konstantinos Slavakis, Shiva Salsabilian, David S. Wack, Sarah Feldt Muldoon, Henry E. Baidoo-Williams, Jean M. Vettel, Matthew Cieslak, Scott T. Grafton
Clustering brain-network-connectivity states using kernel partial correlations. ACSSC (2016)
Ukash Nakarmi, Yihang Zhou, Jingyuan Lyu, Konstantinos Slavakis, Leslie Ying
Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding. ISBI (2016)
Konstantinos Slavakis, Shiva Salsabilian, David S. Wack, Sarah Feldt Muldoon
Clustering time-varying connectivity networks by riemannian geometry: The brain-network case. SSP (2016)
Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis
Spectral clustering of large-scale communities via random sketching and validation. CISS (2015)
Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis
Sketch and Validate for Big Data Clustering. IEEE J. Sel. Top. Signal Process. 9 (4) (2015)
Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis
Large-scale subspace clustering using random sketching and validation. ACSSC (2015)
Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis
Large-scale subspace clustering using sketching and validation. CoRR (2015)
Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis
Sketch and Validate for Big Data Clustering. CoRR (2015)
Xu Wang, Konstantinos Slavakis, Gilad Lerman
Multi-Manifold Modeling in Non-Euclidean spaces. AISTATS (2015)
Konstantinos Slavakis, Seung-Jun Kim, Gonzalo Mateos, Georgios B. Giannakis
Stochastic Approximation vis-a-vis Online Learning for Big Data Analytics [Lecture Notes]. IEEE Signal Process. Mag. 31 (6) (2014)
Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis
Big data clustering via random sketching and validation. ACSSC (2014)
Mahdi Zamanighomi, Zhengdao Wang, Konstantinos Slavakis, Georgios B. Giannakis
Linear minimum mean-square error estimation based on high-dimensional data with missing values. CISS (2014)
Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis
Clustering high-dimensional data via random sampling and consensus. GlobalSIP (2014)
Konstantinos Slavakis, Georgios B. Giannakis, Gonzalo Mateos
Modeling and Optimization for Big Data Analytics: (Statistical) learning tools for our era of data deluge. IEEE Signal Process. Mag. 31 (5) (2014)
Konstantinos Slavakis, Georgios B. Giannakis
Online dictionary learning from big data using accelerated stochastic approximation algorithms. ICASSP (2014)
Xu Wang, Konstantinos Slavakis, Gilad Lerman
Riemannian Multi-Manifold Modeling. CoRR (2014)
Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada
Stochastic Analysis of Hyperslab-Based Adaptive Projected Subgradient Method Under Bounded Noise. IEEE Signal Process. Lett. 20 (7) (2013)
Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis
New operators for fixed-point theory: The sparsity-aware learning case. EUSIPCO (2013)
Konstantinos Slavakis, Isao Yamada
The Adaptive Projected Subgradient Method Constrained by Families of Quasi-nonexpansive Mappings and Its Application to Online Learning. SIAM J. Optim. 23 (1) (2013)
Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis, Georgios B. Giannakis, Vassilis Kekatos
Generalized Iterative Thresholding for Sparsity-Aware Online Volterra System Identification. ISWCS (2013)
Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis, Stephen McLaughlin
Generalized Thresholding and Online Sparsity-Aware Learning in a Union of Subspaces. IEEE Trans. Signal Process. 61 (15) (2013)
Konstantinos Slavakis, Georgios B. Giannakis, Geert Leus
Robust sparse embedding and reconstruction via dictionary learning. CISS (2013)
Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Stephen McLaughlin
Thresholding-based online algorithms of complexity comparable to sparse LMS methods. ISCAS (2013)
Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis
Trading off Complexity With Communication Costs in Distributed Adaptive Learning via Krylov Subspaces for Dimensionality Reduction. IEEE J. Sel. Top. Signal Process. 7 (2) (2013)
Konstantinos Slavakis, Geert Leus, Georgios B. Giannakis
Online robust portfolio risk management using total least-squares and parallel splitting algorithms. ICASSP (2013)
Sergios Theodoridis, Yannis Kopsinis, Konstantinos Slavakis, Symeon Chouvardas
Sparsity-Aware Adaptive Learning: A Set Theoretic Estimation Approach. ALCOSP (2013)
Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Steve McLaughlin
Generalized thresholding sparsity-aware algorithm for low complexity online learning. ICASSP (2012)
Pantelis Bouboulis, Konstantinos Slavakis, Sergios Theodoridis
Adaptive Learning in Complex Reproducing Kernel Hilbert Spaces Employing Wirtinger's Subgradients. IEEE Trans. Neural Networks Learn. Syst. 23 (3) (2012)
Sergios Theodoridis, Yannis Kopsinis, Konstantinos Slavakis
Sparsity-Aware Learning and Compressed Sensing: An Overview CoRR (2012)
Symeon Chouvardas, Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis
A Sparsity Promoting Adaptive Algorithm for Distributed Learning. IEEE Trans. Signal Process. 60 (10) (2012)
Symeon Chouvardas, Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis
Sparsity-promoting adaptive algorithm for distributed learning in diffusion networks. EUSIPCO (2012)
Konstantinos Slavakis, Pantelis Bouboulis, Sergios Theodoridis
Adaptive Multiregression in Reproducing Kernel Hilbert Spaces: The Multiaccess MIMO Channel Case. IEEE Trans. Neural Networks Learn. Syst. 23 (2) (2012)
Sergios Theodoridis, Konstantinos Slavakis, Isao Yamada
Adaptive Learning in a World of Projections. IEEE Signal Process. Mag. 28 (1) (2011)
Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis
Balls. IEEE Trans. Signal Process. 59 (3) (2011)
Symeon Chouvardas, Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis
A Sparsity-Aware Adaptive Algorithm for Distributed Learning CoRR (2011)
Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis
Adaptive Robust Distributed Learning in Diffusion Sensor Networks. IEEE Trans. Signal Process. 59 (10) (2011)
Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis
Trading off communications bandwidth with accuracy in adaptive diffusion networks. ICASSP (2011)
Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis
Robust adaptive sparse system identification by using weighted l1 balls and Moreau envelopes. EUSIPCO (2011)
Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Steve McLaughlin
Reduced complexity online sparse signal reconstruction using projections onto weighted ℓ1 balls. DSP (2011)
Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Steve McLaughlin
Generalized Thresholding Sparsity-Aware Online Learning in a Union of Subspaces CoRR (2011)
Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis
Revisiting adaptive least-squares estimation and application to online sparse signal recovery. ICASSP (2011)
Pantelis Bouboulis, Konstantinos Slavakis, Sergios Theodoridis
Adaptive Kernel-Based Image Denoising Employing Semi-Parametric Regularization. IEEE Trans. Image Process. 19 (6) (2010)
Konstantinos Slavakis, Isao Yamada
Asymptotic minimization of sequences of loss functions constrained by families of quasi-nonexpansive mappings and its application to online learning CoRR (2010)
Pantelis Bouboulis, Sergios Theodoridis, Konstantinos Slavakis
Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces. ICPR (2010)
Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis
Balls CoRR (2010)
Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada
Multi-Domain Adaptive Learning Based on Feasibility Splitting and Adaptive Projected Subgradient Method. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (2) (2010)
Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada
Multi-domain adaptive filtering by feasibility splitting. ICASSP (2010)
Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis
A novel adaptive algorithm for diffusion networks using projections onto hyperslabs. CIP (2010)
Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis
1 balls. ICASSP (2010)
Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada
Signal processing in dual domain by adaptive projected subgradient method. DPS (2009)
Konstantinos Slavakis, Sergios Theodoridis
Affinely constrained online learning and its application to beamforming. ICASSP (2009)
Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada
Adaptive constrained learning in reproducing Kernel Hilbert spaces: the robust beamforming case. IEEE Trans. Signal Process. 57 (12) (2009)
Konstantinos Slavakis, Sergios Theodoridis
Sliding window online Kernel-based classification by projection mappings. ISCAS (2008)
Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada
Robust adaptive nonlinear beamforming by kernels and projection mappings. EUSIPCO (2008)
Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada
Online Kernel-Based Classification Using Adaptive Projection Algorithms. IEEE Trans. Signal Process. 56 (7-1) (2008)
Konstantinos Slavakis, Sergios Theodoridis
Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings. EURASIP J. Adv. Signal Process. 2008 (2008)
Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada
Adaptive Parallel Quadratic-Metric Projection Algorithms. IEEE Trans. Speech Audio Process. 15 (5) (2007)
Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada
Online Kernel-Based Classification by Projections. ICASSP (2) (2007)
Konstantinos Slavakis, Isao Yamada
Robust Wideband Beamforming by the Hybrid Steepest Descent Method. IEEE Trans. Signal Process. 55 (9) (2007)
Florendia Fourli-Kartsouni, Konstantinos Slavakis, Georgios Kouroupetroglou, Sergios Theodoridis
A Bayesian Network Approach to Semantic Labelling of Text Formatting in XML Corpora of Documents. HCI (7) (2007)
Konstantinos Slavakis, Masahiro Yukawa, Isao Yamada
Robust Capon Beamforming by the Adaptive Projected Subgradient Method. ICASSP (4) (2006)
Isao Yamada, Konstantinos Slavakis, Masahiro Yukawa, Renato L. G. Cavalcante
Adaptive projected subgradient method and its applications to robust signal processing. ISCAS (2006)
Konstantinos Slavakis, Isao Yamada, Kohichi Sakaniwa
Computation of symmetric positive definite Toeplitz matrices by the hybrid steepest descent method. Signal Process. 83 (5) (2003)
Konstantinos Slavakis, Isao Yamada, Kohichi Sakaniwa
Spectrum estimation of real vector wide sense stationary processes by the Hybrid Steepest Descent Method. ICASSP (2002)
Isao Yamada, Konstantinos Slavakis, Kenyu Yamada
An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques. IEEE Trans. Signal Process. 50 (5) (2002)
Konstantinos Slavakis, Isao Yamada
Compactly supported matrix valued wavelets-biorthogonal unconditional bases. ISCAS (2) (2001)
Isao Yamada, Konstantinos Slavakis, Kenyu Yamada
An efficient robust adaptive filtering scheme based on parallel subgradient projection techniques. ICASSP (2001)
Konstantinos Slavakis, Isao Yamada
Biorthogonal bases of compactly supported matrix valued wavelets. ISSPA (1999)