Krisztian Buza
Krisztian Buza
Eötvös Lorand University, Budapest, Hungary
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Cited by
Cited by
Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture
RJ Meszlényi, K Buza, Z Vidnyánszky
Frontiers in neuroinformatics 11, 61, 2017
A specialized histone H1 variant is required for adaptive responses to complex abiotic stress and related DNA methylation in Arabidopsis
K Rutowicz, M Puzio, J Halibart-Puzio, M Lirski, M Kotliński, MA Kroteń, ...
Plant Physiology 169 (3), 2080-2101, 2015
Feedback prediction for blogs
K Buza
Data analysis, machine learning and knowledge discovery, 145-152, 2014
Insight: efficient and effective instance selection for time-series classification
K Buza, A Nanopoulos, L Schmidt-Thieme
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 149-160, 2011
Resting state fMRI functional connectivity analysis using dynamic time warping
RJ Meszlényi, P Hermann, K Buza, V Gál, Z Vidnyánszky
Frontiers in neuroscience 11, 75, 2017
Drug-target interaction prediction: a Bayesian ranking approach
L Peska, K Buza, J Koller
Computer methods and programs in biomedicine 152, 15-21, 2017
Motif-based classification of time series with bayesian networks and svms
K Buza, L Schmidt-Thieme
Advances in Data Analysis, Data Handling and Business Intelligence, 105-114, 2009
Success: a new approach for semi-supervised classification of time-series
K Marussy, K Buza
International conference on artificial intelligence and soft computing, 437-447, 2013
Hubness-aware classification, instance selection and feature construction: Survey and extensions to time-series
N Tomašev, K Buza, K Marussy, PB Kis
Feature selection for data and pattern recognition, 231-262, 2015
Nearest neighbor regression in the presence of bad hubs
K Buza, A Nanopoulos, G Nagy
Knowledge-Based Systems 86, 250-260, 2015
Hubness-aware kNN classification of high-dimensional data in presence of label noise
N Tomašev, K Buza
Neurocomputing 160, 157-172, 2015
Scalable event-based clustering of social media via record linkage techniques
T Reuter, P Cimiano, L Drumond, K Buza, L Schmidt-Thieme
Proceedings of the International AAAI Conference on Web and Social Media 5 …, 2011
Drug–target interaction prediction with Bipartite Local Models and hubness-aware regression
K Buza, L Peška
Neurocomputing 260, 284-293, 2017
Storage-optimizing clustering algorithms for high-dimensional tick data
K Buza, GI Nagy, A Nanopoulos
Expert Systems with Applications 41 (9), 4148-4157, 2014
Fusion methods for time-series classification
KA Buza
Peter Lang Verlag, 2011
Folksonomy-based collabulary learning
L Balby Marinho, K Buza, L Schmidt-Thieme
International Semantic Web Conference, 261-276, 2008
Classification of gene expression data: A hubness-aware semi-supervised approach
K Buza
Computer methods and programs in biomedicine 127, 105-113, 2016
Time-series classification based on individualised error prediction
K Buza, A Nanopoulos, L Schmidt-Thieme
2010 13th IEEE International Conference on Computational Science and …, 2010
Classification of fMRI data using dynamic time warping based functional connectivity analysis
R Meszlényi, L Peska, V Gál, Z Vidnyánszky, K Buza
2016 24th European signal processing conference (EUSIPCO), 245-249, 2016
Fusion of similarity measures for time series classification
K Buza, A Nanopoulos, L Schmidt-Thieme
International Conference on Hybrid Artificial Intelligence Systems, 253-261, 2011
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