![](https://dblp.org/img/logo.ua.320x120.png)
![](https://dblp.org/img/dropdown.dark.16x16.png)
![](https://dblp.org/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.org/img/search.dark.16x16.png)
![search dblp](https://dblp.org/img/search.dark.16x16.png)
default search action
Konstantinos Slavakis
Person information
Refine list
![note](https://dblp.org/img/note-mark.dark.12x12.png)
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c51]Yuki Akiyama, Konstantinos Slavakis:
Proximal Bellman Mappings for Reinforcement Learning and Their Application to Robust Adaptive Filtering. ICASSP 2024: 5855-5859 - [c50]Duc Thien Nguyen, Konstantinos Slavakis:
Multi-Linear Kernel Regression and Imputation VIA Manifold Learning: the Dynamic MRI Case. ICASSP 2024: 9466-9470 - [i20]Duc Thien Nguyen, Konstantinos Slavakis:
Multilinear Kernel Regression and Imputation via Manifold Learning. CoRR abs/2402.03648 (2024) - [i19]Yuki Akiyama, Minh Vu, Konstantinos Slavakis:
Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering. CoRR abs/2403.20020 (2024) - 2023
- [c49]Minh Vu, Yuki Akiyama, Konstantinos Slavakis:
Dynamic Selection of p-norm in Linear Adaptive Filtering via online Kernel-based Reinforcement Learning. ICASSP 2023: 1-5 - [i18]Duc Thien Nguyen, Konstantinos Slavakis:
Multi-Linear Kernel Regression and Imputation in Data Manifolds. CoRR abs/2304.03041 (2023) - [i17]Yuki Akiyama, Konstantinos Slavakis:
Proximal Bellman mappings for reinforcement learning and their application to robust adaptive filtering. CoRR abs/2309.07548 (2023) - 2022
- [j28]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: 133-147 (2022) - [d1]Konstantinos Slavakis
, Gaurav N. Shetty:
Kernel Regression Imputation in Manifolds: Videos of dMRI data. IEEE DataPort, 2022 - [i16]Minh Vu, Yuki Akiyama, Konstantinos Slavakis:
Dynamic selection of p-norm in linear adaptive filtering via online kernel-based reinforcement learning. CoRR abs/2210.11317 (2022) - [i15]Yuki Akiyama, Minh Vu, Konstantinos Slavakis:
online and lightweight kernel-based approximated policy iteration for dynamic p-norm linear adaptive filtering. CoRR abs/2210.11755 (2022) - 2021
- [j27]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: 107834 (2021) - [c48]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: 3815-3819 - [c47]Konstantinos Slavakis, Masahiro Yukawa:
Outlier-Robust Kernel Hierarchical-Optimization RLS on a Budget with Affine Constraints. ICASSP 2021: 5335-5339 - 2020
- [j26]Konstantinos Slavakis
, Sinjini Banerjee
:
Robust Hierarchical-Optimization RLS Against Sparse Outliers. IEEE Signal Process. Lett. 27: 171-175 (2020) - [j25]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): 688-702 (2020) - [c46]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: 1482-1486 - [i14]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 abs/2002.09943 (2020) - [i13]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 abs/2002.11885 (2020)
2010 – 2019
- 2019
- [j24]Konstantinos Slavakis
:
The Stochastic Fejér-Monotone Hybrid Steepest Descent Method and the Hierarchical RLS. IEEE Trans. Signal Process. 67(11): 2868-2883 (2019) - [i12]Cong Ye, Konstantinos Slavakis, Pratik V. Patil, Sarah Feldt Muldoon, John D. Medaglia:
Brain-Network Clustering via Kernel-ARMA Modeling and the Grassmannian. CoRR abs/1906.02292 (2019) - [i11]Konstantinos Slavakis, Sinjini Banerjee:
Robust Hierarchical-Optimization RLS Against Sparse Outliers. CoRR abs/1910.05399 (2019) - 2018
- [j23]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): 519-533 (2018) - [c45]Konstantinos Slavakis:
Stochastic Composite Convex Minimization with Affine Constraints. ACSSC 2018: 1871-1875 - [c44]Konstantinos Slavakis, Aritra Konar, Nicholas D. Sidiropoulos
:
Fast Projection-Based Solvers for the Non-Convex Quadratically Constrained Feasibility Problem. ICASSP 2018: 3954-3958 - [c43]Ukash Nakarmi, Konstantinos Slavakis, Leslie Ying
:
MLS: Joint manifold-learning and sparsity-aware framework for highly accelerated dynamic magnetic resonance imaging. ISBI 2018: 1213-1216 - [i10]Gaurav N. Shetty, Konstantinos Slavakis, Abhishek Bose, Ukash Nakarmi, Leslie Ying, Gesualdo Scutari:
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery. CoRR abs/1812.10617 (2018) - 2017
- [c42]Konstantinos Slavakis, Gaurav N. Shetty, Abhishek Bose, Ukash Nakarmi, Leslie Ying
:
Bi-Linear modeling of manifold-data geometry for Dynamic-MRI recovery. CAMSAP 2017: 1-5 - [c41]Konstantinos Slavakis, Isao Yamada, Shunsuke Ono:
Accelerating the hybrid steepest descent method for affinely constrained convex composite minimization tasks. ICASSP 2017: 4711-4715 - [c40]Ukash Nakarmi, Konstantinos Slavakis, Jingyuan Lyu, Leslie Ying
:
M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging. ISBI 2017: 19-22 - [i9]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 abs/1701.07767 (2017) - 2016
- [c39]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: 268-272 - [c38]G. V. Karanikolas, Georgios B. Giannakis
, Konstantinos Slavakis, Richard M. Leahy:
Multi-kernel based nonlinear models for connectivity identification of brain networks. ICASSP 2016: 6315-6319 - [c37]Ukash Nakarmi, Yihang Zhou
, Jingyuan Lyu, Konstantinos Slavakis, Leslie Ying
:
Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding. ISBI 2016: 510-513 - [c36]Konstantinos Slavakis, Shiva Salsabilian, David S. Wack, Sarah Feldt Muldoon
:
Clustering time-varying connectivity networks by riemannian geometry: The brain-network case. SSP 2016: 1-5 - 2015
- [j22]Panagiotis A. Traganitis
, Konstantinos Slavakis, Georgios B. Giannakis
:
Sketch and Validate for Big Data Clustering. IEEE J. Sel. Top. Signal Process. 9(4): 678-690 (2015) - [c35]Panagiotis A. Traganitis
, Konstantinos Slavakis, Georgios B. Giannakis
:
Large-scale subspace clustering using random sketching and validation. ACSSC 2015: 107-111 - [c34]Xu Wang, Konstantinos Slavakis, Gilad Lerman:
Multi-Manifold Modeling in Non-Euclidean spaces. AISTATS 2015 - [c33]Panagiotis A. Traganitis
, Konstantinos Slavakis, Georgios B. Giannakis
:
Spectral clustering of large-scale communities via random sketching and validation. CISS 2015: 1-6 - [i8]Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis:
Sketch and Validate for Big Data Clustering. CoRR abs/1501.05590 (2015) - [i7]Panagiotis A. Traganitis, Konstantinos Slavakis, Georgios B. Giannakis:
Large-scale subspace clustering using sketching and validation. CoRR abs/1510.01628 (2015) - 2014
- [j21]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): 18-31 (2014) - [j20]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): 124-129 (2014) - [c32]Panagiotis A. Traganitis
, Konstantinos Slavakis, Georgios B. Giannakis
:
Big data clustering via random sketching and validation. ACSSC 2014: 1046-1050 - [c31]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: 1-5 - [c30]Panagiotis A. Traganitis
, Konstantinos Slavakis, Georgios B. Giannakis
:
Clustering high-dimensional data via random sampling and consensus. GlobalSIP 2014: 307-311 - [c29]Konstantinos Slavakis, Georgios B. Giannakis
:
Online dictionary learning from big data using accelerated stochastic approximation algorithms. ICASSP 2014: 16-20 - [i6]Xu Wang, Konstantinos Slavakis, Gilad Lerman:
Riemannian Multi-Manifold Modeling. CoRR abs/1410.0095 (2014) - 2013
- [j19]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): 257-273 (2013) - [j18]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): 126-152 (2013) - [j17]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): 729-732 (2013) - [j16]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): 3760-3773 (2013) - [c28]Sergios Theodoridis, Yannis Kopsinis, Konstantinos Slavakis, Symeon Chouvardas:
Sparsity-Aware Adaptive Learning: A Set Theoretic Estimation Approach. ALCOSP 2013: 748-756 - [c27]Konstantinos Slavakis, Georgios B. Giannakis
, Geert Leus
:
Robust sparse embedding and reconstruction via dictionary learning. CISS 2013: 1-6 - [c26]Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis:
New operators for fixed-point theory: The sparsity-aware learning case. EUSIPCO 2013: 1-5 - [c25]Konstantinos Slavakis, Geert Leus
, Georgios B. Giannakis
:
Online robust portfolio risk management using total least-squares and parallel splitting algorithms. ICASSP 2013: 5686-5690 - [c24]Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Stephen McLaughlin
:
Thresholding-based online algorithms of complexity comparable to sparse LMS methods. ISCAS 2013: 513-516 - [c23]Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis, Georgios B. Giannakis, Vassilis Kekatos:
Generalized Iterative Thresholding for Sparsity-Aware Online Volterra System Identification. ISWCS 2013: 1-5 - 2012
- [j15]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): 260-276 (2012) - [j14]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): 425-438 (2012) - [j13]Symeon Chouvardas, Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis:
A Sparsity Promoting Adaptive Algorithm for Distributed Learning. IEEE Trans. Signal Process. 60(10): 5412-5425 (2012) - [c22]Symeon Chouvardas, Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis:
Sparsity-promoting adaptive algorithm for distributed learning in diffusion networks. EUSIPCO 2012: 1084-1088 - [c21]Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Steve McLaughlin
:
Generalized thresholding sparsity-aware algorithm for low complexity online learning. ICASSP 2012: 3277-3280 - [i5]Sergios Theodoridis, Yannis Kopsinis, Konstantinos Slavakis:
Sparsity-Aware Learning and Compressed Sensing: An Overview. CoRR abs/1211.5231 (2012) - 2011
- [j12]Sergios Theodoridis, Konstantinos Slavakis, Isao Yamada:
Adaptive Learning in a World of Projections. IEEE Signal Process. Mag. 28(1): 97-123 (2011) - [j11]Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis:
Online Sparse System Identification and Signal Reconstruction Using Projections Onto Weighted ell1 Balls. IEEE Trans. Signal Process. 59(3): 936-952 (2011) - [j10]Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis:
Adaptive Robust Distributed Learning in Diffusion Sensor Networks. IEEE Trans. Signal Process. 59(10): 4692-4707 (2011) - [c20]Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis:
Robust adaptive sparse system identification by using weighted l1 balls and Moreau envelopes. EUSIPCO 2011: 1924-1928 - [c19]Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis:
Trading off communications bandwidth with accuracy in adaptive diffusion networks. ICASSP 2011: 2048-2051 - [c18]Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis:
Revisiting adaptive least-squares estimation and application to online sparse signal recovery. ICASSP 2011: 4292-4295 - [c17]Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Steve McLaughlin
:
Reduced complexity online sparse signal reconstruction using projections onto weighted ℓ1 balls. DSP 2011: 1-8 - [i4]Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Steve McLaughlin
:
Generalized Thresholding Sparsity-Aware Online Learning in a Union of Subspaces. CoRR abs/1112.0665 (2011) - [i3]Symeon Chouvardas, Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis:
A Sparsity-Aware Adaptive Algorithm for Distributed Learning. CoRR abs/1112.5716 (2011) - 2010
- [j9]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. 93-A(2): 456-466 (2010) - [j8]Pantelis Bouboulis, Konstantinos Slavakis, Sergios Theodoridis:
Adaptive Kernel-Based Image Denoising Employing Semi-Parametric Regularization. IEEE Trans. Image Process. 19(6): 1465-1479 (2010) - [c16]Symeon Chouvardas, Konstantinos Slavakis, Sergios Theodoridis:
A novel adaptive algorithm for diffusion networks using projections onto hyperslabs. CIP 2010: 393-398 - [c15]Konstantinos Slavakis, Yannis Kopsinis, Sergios Theodoridis:
Adaptive algorithm for sparse system identification using projections onto weighted l1 balls. ICASSP 2010: 3742-3745 - [c14]Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada:
Multi-domain adaptive filtering by feasibility splitting. ICASSP 2010: 3814-3817 - [c13]Pantelis Bouboulis, Sergios Theodoridis, Konstantinos Slavakis:
Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces. ICPR 2010: 2660-2663 - [i2]Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis:
Online Sparse System Identification and Signal Reconstruction using Projections onto Weighted ℓ1 Balls. CoRR abs/1004.3040 (2010) - [i1]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 abs/1008.5231 (2010)
2000 – 2009
- 2009
- [j7]Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada:
Adaptive constrained learning in reproducing Kernel Hilbert spaces: the robust beamforming case. IEEE Trans. Signal Process. 57(12): 4744-4764 (2009) - [c12]Konstantinos Slavakis, Sergios Theodoridis:
Affinely constrained online learning and its application to beamforming. ICASSP 2009: 1573-1576 - [c11]Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada:
Signal processing in dual domain by adaptive projected subgradient method. DPS 2009: 1-6 - 2008
- [j6]Konstantinos Slavakis, Sergios Theodoridis:
Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings. EURASIP J. Adv. Signal Process. 2008 (2008) - [j5]Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada:
Online Kernel-Based Classification Using Adaptive Projection Algorithms. IEEE Trans. Signal Process. 56(7-1): 2781-2796 (2008) - [c10]Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada:
Robust adaptive nonlinear beamforming by kernels and projection mappings. EUSIPCO 2008: 1-5 - [c9]Konstantinos Slavakis, Sergios Theodoridis:
Sliding window online Kernel-based classification by projection mappings. ISCAS 2008: 49-52 - 2007
- [j4]Masahiro Yukawa, Konstantinos Slavakis, Isao Yamada:
Adaptive Parallel Quadratic-Metric Projection Algorithms. IEEE Trans. Speech Audio Process. 15(5): 1665-1680 (2007) - [j3]Konstantinos Slavakis, Isao Yamada:
Robust Wideband Beamforming by the Hybrid Steepest Descent Method. IEEE Trans. Signal Process. 55(9): 4511-4522 (2007) - [c8]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: 299-308 - [c7]Konstantinos Slavakis, Sergios Theodoridis, Isao Yamada:
Online Kernel-Based Classification by Projections. ICASSP (2) 2007: 425-428 - 2006
- [c6]Konstantinos Slavakis, Masahiro Yukawa, Isao Yamada:
Robust Capon Beamforming by the Adaptive Projected Subgradient Method. ICASSP (4) 2006: 1005-1008 - [c5]Isao Yamada, Konstantinos Slavakis, Masahiro Yukawa, Renato L. G. Cavalcante:
Adaptive projected subgradient method and its applications to robust signal processing. ISCAS 2006 - 2003
- [j2]Konstantinos Slavakis, Isao Yamada, Kohichi Sakaniwa:
Computation of symmetric positive definite Toeplitz matrices by the hybrid steepest descent method. Signal Process. 83(5): 1135-1140 (2003) - 2002
- [j1]Isao Yamada, Konstantinos Slavakis, Kenyu Yamada:
An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques. IEEE Trans. Signal Process. 50(5): 1091-1101 (2002) - [c4]Konstantinos Slavakis, Isao Yamada, Kohichi Sakaniwa:
Spectrum estimation of real vector wide sense stationary processes by the Hybrid Steepest Descent Method. ICASSP 2002: 1357-1360 - 2001
- [c3]Isao Yamada, Konstantinos Slavakis, Kenyu Yamada:
An efficient robust adaptive filtering scheme based on parallel subgradient projection techniques. ICASSP 2001: 3725-3728 - [c2]Konstantinos Slavakis, Isao Yamada:
Compactly supported matrix valued wavelets-biorthogonal unconditional bases. ISCAS (2) 2001: 485-488
1990 – 1999
- 1999
- [c1]Konstantinos Slavakis, Isao Yamada:
Biorthogonal bases of compactly supported matrix valued wavelets. ISSPA 1999: 981-984
Coauthor Index
![](https://dblp.org/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-07 21:33 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint