Aristidis Likas - researchr alias

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2011

Document clustering using synthetic cluster prototypesArgyris Kalogeratos, Aristidis Likas. DKE, 70(3):284-306, 2011. [doi]

Visual tracking using the Earth Mover s Distance between Gaussian mixtures and Kalman filteringVasileios Karavasilis, Christophoros Nikou, Aristidis Likas. ivc, 29(5):295-305, 2011. [doi]

Efficiently Explaining Decisions of Probabilistic RBF Classification NetworksMarko Robnik-Sikonja, Aristidis Likas, Constantinos Constantinopoulos, Igor Kononenko, Erik Strumbelj. icannga 2011: 169-179 [doi]

2010

2009

Movie segmentation into scenes and chapters using locally weighted bag of visual wordsVasileios Chasanis, Argyris Kalogeratos, Aristidis Likas. civr 2009: [doi]

Simultaneous detection of abrupt cuts and dissolves in videos using support vector machinesVasileios Chasanis, Aristidis Likas, Nikolas P. Galatsanos. prl, 30(1):55-65, 2009. [doi]

Scene Detection in Videos Using Shot Clustering and Sequence AlignmentVasileios Chasanis, Aristidis Likas, Nikolas P. Galatsanos. tmm, 11(1):89-100, 2009. [doi]

The mixtures of Student s t-distributions as a robust framework for rigid registrationDemetrios Gerogiannis, Christophoros Nikou, Aristidis Likas. ivc, 27(9):1285-1294, 2009. [doi]

Combining Gaussian Mixture Models and Support Vector Machines for Relevance Feedback in Content Based Image RetrievalApostolos Marakakis, Nikolas P. Galatsanos, Aristidis Likas, Andreas Stafylopatis. ifip12 2009: 249-258 [doi]

Relevance Feedback for Content-Based Image Retrieval Using Support Vector Machines and Feature SelectionApostolos Marakakis, Nikolas P. Galatsanos, Aristidis Likas, Andreas Stafylopatis. icann 2009: 942-951 [doi]

Local Feature Selection for the Relevance Vector Machine Using Adaptive Kernel LearningDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. icann 2009: 50-59 [doi]

Variational Bayesian Sparse Kernel-Based Blind Image Deconvolution With Student s-t PriorsDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. TIP, 18(4):753-764, 2009. [doi]

Sparse Bayesian Modeling With Adaptive Kernel LearningDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. tnn, 20(6):926-937, 2009. [doi]

Convex Mixture Models for Multi-view ClusteringGrigorios Tzortzis, Aristidis Likas. icann 2009: 205-214 [doi]

The Global Kernel k -Means Algorithm for Clustering in Feature SpaceGrigorios Tzortzis, Aristidis Likas. tnn, 20(7):1181-1194, 2009. [doi]

2008

Probabilistic Models Based on the Pi-Sigmoid DistributionAnastasios Alivanoglou, Aristidis Likas. annpr 2008: 36-43 [doi]

A Sparse Regression Mixture Model for Clustering Time-SeriesKonstantinos Blekas, Nikolas P. Galatsanos, Aristidis Likas. setn 2008: 64-72 [doi]

Variational Bayesian Image Restoration Based on a Product of t-Distributions Image PriorGiannis K. Chantas, Nikolas P. Galatsanos, Aristidis Likas, Michael Saunders. TIP, 17(10):1795-1805, 2008. [doi]

Video rushes summarization using spectral clustering and sequence alignmentVasileios Chasanis, Aristidis Likas, Nikolas P. Galatsanos. mm 2008: 75-79 [doi]

Efficient Video Shot Summarization Using an Enhanced Spectral Clustering ApproachVasileios Chasanis, Aristidis Likas, Nikolas P. Galatsanos. icann 2008: 847-856 [doi]

A Support Vector Machine Approach for Video Shot DetectionVasileios Chasanis, Aristidis Likas, Nikolas P. Galatsanos. In George A. Tsihrintzis, Maria Virvou, Robert J. Howlett, Lakhmi C. Jain, editors, New Directions in Intelligent Interactive Multimedia. Volume 142 of Studies in Computational Intelligence, pages 45-54, Springer, 2008. [doi]

Application of Relevance Feedback in Content Based Image Retrieval Using Gaussian Mixture ModelsApostolos Marakakis, Nikolas P. Galatsanos, Aristidis Likas, Andreas Stafylopatis. ictai 2008: 141-148 [doi]

Incremental Relevance Vector Machine with Kernel LearningDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. setn 2008: 301-312 [doi]

The global kernel k-means clustering algorithmGrigorios Tzortzis, Aristidis Likas. ijcnn 2008: 1977-1984 [doi]

2007

Unsupervised Learning of Gaussian Mixtures Based on Variational Component SplittingConstantinos Constantinopoulos, Aristidis Likas. tnn, 18(3):745-755, 2007. [doi]

Image Modeling and Segmentation Using Incremental Bayesian Mixture ModelsConstantinos Constantinopoulos, Aristidis Likas. caip 2007: 596-603 [doi]

Robust Image Registration using Mixtures of t-distributionsDemetrios Gerogiannis, Christophoros Nikou, Aristidis Likas. iccv 2007: 1-8 [doi]

Rigid Image Registration based on Pixel GroupingDemetrios Gerogiannis, Christophoros Nikou, Aristidis Likas. iciap 2007: 595-602 [doi]

Bayesian Kernel Methods for Analysis of Functional NeuroimagesAna S. Lukic, Miles N. Wernick, Dimitris Tzikas, X. Chen, Aristidis Likas, Nikolas P. Galatsanos, Yongyi Yang, E. Zhao, Stephen C. Strother. tmi, 26(12):1613-1624, 2007. [doi]

A Class-Adaptive Spatially Variant Mixture Model for Image SegmentationChristophoros Nikou, Nikolas P. Galatsanos, Aristidis Likas. TIP, 16(4):1121-1130, 2007. [doi]

Variational Bayesian Blind Image Deconvolution with Student-T PriorsDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. icip 2007: 109-112 [doi]

Large Scale Multikernel Relevance Vector Machine for Object DetectionDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. ijait, 16(6):967-979, 2007. [doi]

Robust variational bayesian kernel based blind image deconvolutionDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. visapp 2007: 143-150

Transductive Reliability Estimation for Kernel Based ClassifiersDimitris Tzikas, Matjaz Kukar, Aristidis Likas. ida 2007: 37-47 [doi]

Deep Belief Networks for Spam FilteringGrigorios Tzortzis, Aristidis Likas. ictai 2007: 306-309 [doi]

2006

Bayesian Restoration Using a New Nonstationary Edge-Preserving Image PriorGiannis K. Chantas, Nikolas P. Galatsanos, Aristidis Likas. TIP, 15(10):2987-2997, 2006. [doi]

Active Learning with the Probabilistic RBF ClassifierConstantinos Constantinopoulos, Aristidis Likas. icann 2006: 357-366 [doi]

An incremental training method for the probabilistic RBF networkConstantinos Constantinopoulos, Aristidis Likas. tnn, 17(4):966-974, 2006. [doi]

Bayesian Feature and Model Selection for Gaussian Mixture ModelsConstantinos Constantinopoulos, Michalis K. Titsias, Aristidis Likas. pami, 28(6):1013-1018, 2006. [doi]

A Significance-Based Graph Model for Clustering Web DocumentsArgyris Kalogeratos, Aristidis Likas. setn 2006: 516-519 [doi]

A novel method for automated EMG decomposition and MUAP classificationC. D. Katsis, Yorgos Goletsis, Aristidis Likas, Dimitrios I. Fotiadis, I. Sarmas. artmed, 37(1):55-64, 2006. [doi]

A Relevance Feedback Approach for Content Based Image Retrieval Using Gaussian Mixture ModelsApostolos Marakakis, Nikolas P. Galatsanos, Aristidis Likas, Andreas Stafylopatis. icann (empty year): 84-93 [doi]

Large Scale Multikernel RVM for Object DetectionDimitris Tzikas, Aristidis Likas, Nikolas P. Galatsanos. setn 2006: 389-399 [doi]

2005

Semantics-based information modeling for the health-care administration sector: the Citation platformA. G. Anagnostakis, M. Tzima, G. C. Sakellaris, Dimitrios I. Fotiadis, Aristidis Likas. titb, 9(2):239-247, 2005. [doi]

A Spatially-Constrained Mixture Model for Image SegmentationBlekas, K., Likas, A., Galatsanos, N. P., Lagaris. I.E., Konstantinos Blekas, Aristidis Likas, A., Nikolas P. Galatsanos, I. E. Lagaris. IEEE Tansactions on Neural Networks, 16:494-498, 2005.

Motif-Based Protein Sequence Classification Using Neural NetworksKonstantinos Blekas, Dimitrios I. Fotiadis, Aristidis Likas. jcb, 12(1):64-82, 2005. [doi]

Mixture model analysis of DNA microarray imagesKonstantinos Blekas, Nikolas P. Galatsanos, Aristidis Likas, Isaac E. Lagaris. tmi, 24(7):901-909, 2005. [doi]

Maximum a posteriori image restoration based on a new directional continuous edge image priorJohn Chantas, Nikolas P. Galatsanos, Aristidis Likas. icip 2005: 941-944 [doi]

Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machinesAthanasios Papadopoulos, Dimitrios I. Fotiadis, Aristidis Likas. artmed, 34(2):141-150, 2005. [doi]

An Analytic Distance Metric for Gaussian Mixture Models with Application in Image RetrievalGiorgos Sfikas, Constantinos Constantinopoulos, Aristidis Likas, Nikolas P. Galatsanos. icann 2005: 835-840 [doi]

Neural Splines: Exploiting Parallelism for Fuction Approximation Using Modular Neural NetworksIoannis G. Tsoulos, Isaac E. Lagaris, Aristidis Likas. npsc, 13:161-178, 2005.

2004

2003

Protein Sequence Classification Using Probabilistic Motifs and Neural NetworksKonstantinos Blekas, Dimitrios I. Fotiadis, Aristidis Likas. icann 2003: 702-709 [doi]

Greedy mixture learning for multiple motif discovery in biological sequencesKonstantinos Blekas, Dimitrios I. Fotiadis, Aristidis Likas. bioinformatics, 19(5):607-617, 2003.

A divide-and-conquer method for multi-net classifiersDimitrios Frosyniotis, Andreas Stafylopatis, Aristidis Likas. paa, 6(1):32-40, 2003. [doi]

The global k-means clustering algorithmAristidis Likas, Nikos A. Vlassis, Jakob J. Verbeek. PR, 36(2):451-461, 2003. [doi]

A variational method for Bayesian blind image deconvolutionAristidis Likas, Nikolas P. Galatsanos. icip 2003: 973-976

Class Conditional Density Estimation Using Mixtures with Constrained Component SharingMichalis K. Titsias, Aristidis Likas. pami, 25(7):924-928, 2003. [doi]

2002

CITATION - Citizen Information Tool in Smart AdministrationA. G. Anagnostakis, G. C. Sakellaris, M. Tzima, Dimitrios I. Fotiadis, Aristidis Likas. egov 2002: 307-312 [doi]

The Citation Platform: Semantics-Based Modeling & Retrieval of Administrative InformationA. G. Anagnostakis, G. C. Sakellaris, M. Tzima, Dimitrios I. Fotiadis, Aristidis Likas. iadis 2002: 577-583

A Bayesian Regularization Method for the Probabilistic RBF NetworkConstantinos Constantinopoulos, Michalis K. Titsias, Aristidis Likas. setn 2002: 337-345 [doi]

An automatic microcalcification detection system based on a hybrid neural network classifierAthanasios Papadopoulos, Dimitrios I. Fotiadis, Aristidis Likas. artmed, 25(2):149-167, 2002.

An ischemia detection method based on artificial neural networksCostas Papaloukas, Dimitrios I. Fotiadis, Aristidis Likas, Lampros K. Michalis. artmed, 24(2):167-178, 2002.

Mixture of Experts Classification Using a Hierarchical Mixture ModelMichalis K. Titsias, Aristidis Likas. neco, 14(9):2221-2244, 2002. [doi]

Piecewise Neural Networks for Function Approximation, Cast in a Form Suitable for Parallel ComputationIoannis G. Tsoulos, Isaac E. Lagaris, Aristidis Likas. setn 2002: 314-324 [doi]

A Greedy EM Algorithm for Gaussian Mixture LearningNikos A. Vlassis, Aristidis Likas. npl, 15(1):77-87, 2002.

2001

Reinforcement Learning Using the Stochastic Fuzzy Min-Max Neural NetworkAristidis Likas. npl, 13(3):213-220, 2001.

2000

Training the random neural network using quasi-Newton methodsAristidis Likas, Andreas Stafylopatis. eor, 126(2):331-339, 2000. [doi]

A robust knowledge-based technique for ischemia detection in noisy ECGsCostas Papaloukas, Dimitrios I. Fotiadis, Aristidis Likas, Athanasios P. Liavas, Lampros K. Michalis. kes 2000: 768-771 [doi]

A Probabilistic RBF Network for ClassificationMichalis K. Titsias, Aristidis Likas. ijcnn 2000: 238-243 [doi]

1999

Training Reinforcement Neurocontrollers Using the Polytope AlgorithmAristidis Likas, Isaac E. Lagaris. npl, 9(2):119-127, 1999.

A Reinforcement Learning Approach to Online ClusteringAristidis Likas. neco, 11(8):1915-1932, 1999.

A kurtosis-based dynamic approach to Gaussian mixture modelingNikos A. Vlassis, Aristidis Likas. tsmc, 29(4):393-399, 1999.

1998

Artificial neural networks for solving ordinary and partial differential equationsIsaac E. Lagaris, Aristidis Likas, Dimitrios I. Fotiadis. tnn, 9(5):987-1000, 1998. [doi]

1997

A Fuzzy Neural Network Approach to Classification Based on Proximity Characteristics of PatternsKonstantinos Blekas, Aristidis Likas, Andreas Stafylopatis. ictai 1997: 323-330 [doi]

A Connectionist Approach for Solving Large Constraint Satisfaction ProblemsAristidis Likas, George Papageorgiou, Andreas Stafylopatis. apin, 7(3):215-225, 1997.

1996

A Reinforcement Learning Approach Based on the Fuzzy Min-Max Neural NetworkAristidis Likas, Konstantinos Blekas. npl, 4(3):167-172, 1996.

High Capacity Associative Memory Based on The Random Neural Network ModelAristidis Likas, Andreas Stafylopatis. ijprai, 10(8):919-937, 1996.

1995

Discrete Optimisation Based on the Combined Use of Reinforcement and Constraint Satisfaction SchemesD. Kontoravdis, Aristidis Likas, Andreas Stafylopatis. nca, 3(2):101-112, 1995.

A Parallel Algorithm for the Minimum Weighted Vertex Cover ProblemAristidis Likas, Andreas Stafylopatis. ipl, 53(4):229-234, 1995. [doi]

Parallel Recombinative Reinforcement Learning (Extended Abstract)Aristidis Likas, Konstantinos Blekas, Andreas Stafylopatis. ecml 1995: 311-314

1992

Collision-Free Movement of an Autonomous Vehicle Using Reinforcement LearningD. Kontoravdis, Aristidis Likas, Andreas Stafylopatis. ecai 1992: 666-670

Pictorial Information Retrieval Using the Random Neural NetworkAndreas Stafylopatis, Aristidis Likas. TSE, 18(7):590-600, 1992. [doi]