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- affiliation: Eindhoven University of Technology, Netherlands
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2020 – today
- 2021
[j42]Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet:
Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency. Data Min. Knowl. Discov. 35(3): 796-836 (2021)- [j41]Ghada Sokar, Decebal Constantin Mocanu
, Mykola Pechenizkiy:
SpaceNet: Make Free Space for Continual Learning. Neurocomputing 439: 1-11 (2021) - [j40]Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy:
Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware. Neural Comput. Appl. 33(7): 2589-2604 (2021) - [j39]Toon Calders, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Salvatore Ruggieri:
Introduction to The Special Section on Bias and Fairness in AI. SIGKDD Explor. 23(1): 1-3 (2021) - [c128]Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Self-Attention Meta-Learner for Continual Learning. AAMAS 2021: 1658-1660 - [c127]Akrati Saxena, George Fletcher, Mykola Pechenizkiy:
How Fair is Fairness-aware Representative Ranking? WWW (Companion Volume) 2021: 161-165 - [i39]Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Learning Invariant Representation for Continual Learning. CoRR abs/2101.06162 (2021) - [i38]Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy:
Selfish Sparse RNN Training. CoRR abs/2101.09048 (2021) - [i37]Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Self-Attention Meta-Learner for Continual Learning. CoRR abs/2101.12136 (2021) - [i36]Akrati Saxena, George Fletcher, Mykola Pechenizkiy:
NodeSim: Node Similarity based Network Embedding for Diverse Link Prediction. CoRR abs/2102.00785 (2021) - [i35]Selima Curci, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Truly Sparse Neural Networks at Scale. CoRR abs/2102.01732 (2021) - [i34]Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. CoRR abs/2102.02887 (2021) - [i33]Akrati Saxena, George Fletcher, Mykola Pechenizkiy:
How Fair is Fairness-aware Representative Ranking and Methods for Fair Ranking. CoRR abs/2103.01335 (2021) - [i32]Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy:
Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks. CoRR abs/2104.07917 (2021) - [i31]Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy:
Direction-Aggregated Attack for Transferable Adversarial Examples. CoRR abs/2104.09172 (2021) - [i30]Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone:
Dynamic Sparse Training for Deep Reinforcement Learning. CoRR abs/2106.04217 (2021) - 2020
- [j38]José María Luna, Mykola Pechenizkiy, Wouter Duivesteijn, Sebastián Ventura:
Exceptional in so Many Ways - Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios. IEEE Access 8: 200982-200994 (2020) - [j37]Sanna Järvelä, Dragan Gasevic, Tapio Seppänen, Mykola Pechenizkiy, Paul A. Kirschner:
Bridging learning sciences, machine learning and affective computing for understanding cognition and affect in collaborative learning. Br. J. Educ. Technol. 51(6): 2391-2406 (2020) - [j36]Negar Ahmadi, Yulong Pei, Evelien Carrette, Albert P. Aldenkamp, Mykola Pechenizkiy:
EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features. Brain Informatics 7(1): 6 (2020) - [j35]Yulong Pei, Xin Du, Jianpeng Zhang, George Fletcher, Mykola Pechenizkiy:
struc2gauss: Structural role preserving network embedding via Gaussian embedding. Data Min. Knowl. Discov. 34(4): 1072-1103 (2020) - [j34]Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy:
Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling. Data Min. Knowl. Discov. 34(5): 1267-1290 (2020) - [j33]Yingjun Deng, Alessandro Di Bucchianico, Mykola Pechenizkiy:
Controlling the accuracy and uncertainty trade-off in RUL prediction with a surrogate Wiener propagation model. Reliab. Eng. Syst. Saf. 196: 106727 (2020) - [j32]Jianpeng Zhang, Yulong Pei, George Fletcher, Mykola Pechenizkiy:
Evaluation of the Sample Clustering Process on Graphs. IEEE Trans. Knowl. Data Eng. 32(7): 1333-1347 (2020) - [c126]Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy:
Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data. AAAI 2020: 3809-3816 - [c125]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
Feedback Loop and Bias Amplification in Recommender Systems. CIKM 2020: 2145-2148 - [c124]Afrizal Doewes, Mykola Pechenizkiy:
Structural Explanation of Automated Essay Scoring. EDM 2020 - [c123]Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher:
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. FLAIRS Conference 2020: 193-196 - [c122]Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George Fletcher, Mykola Pechenizkiy:
Novelty producing synaptic plasticity. GECCO Companion 2020: 93-94 - [c121]Mostafa Mohammadpourfard, Fateme Ghanaatpishe, Marziyeh Mohammadi, Subhash Lakshminarayana, Mykola Pechenizkiy:
Generation of False Data Injection Attacks using Conditional Generative Adversarial Networks. ISGT-Europe 2020: 41-45 - [c120]Ricky Maulana Fajri, Samaneh Khoshrou, Robert Peharz, Mykola Pechenizkiy:
PS3: Partition-Based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data. ECML/PKDD (5) 2020: 68-84 - [c119]Lu Yin, Vlado Menkovski, Mykola Pechenizkiy:
Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing. ECML/PKDD (2) 2020: 154-169 - [c118]Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu:
Topological Insights into Sparse Neural Networks. ECML/PKDD (3) 2020: 279-294 - [c117]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. UMAP 2020: 154-162 - [i29]Yuhao Wang, Vlado Menkovski, Hao Wang, Xin Du, Mykola Pechenizkiy:
Causal Discovery from Incomplete Data: A Deep Learning Approach. CoRR abs/2001.05343 (2020) - [i28]Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy:
Novelty Producing Synaptic Plasticity. CoRR abs/2002.03620 (2020) - [i27]Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher:
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. CoRR abs/2002.07786 (2020) - [i26]Lu Yin, Vlado Menkovski, Mykola Pechenizkiy:
Knowledge Elicitation using Deep Metric Learning and Psychometric Testing. CoRR abs/2004.06353 (2020) - [i25]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. CoRR abs/2005.01148 (2020) - [i24]Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu:
Topological Insights in Sparse Neural Networks. CoRR abs/2006.14085 (2020) - [i23]Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy:
SpaceNet: Make Free Space For Continual Learning. CoRR abs/2007.07617 (2020) - [i22]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
Feedback Loop and Bias Amplification in Recommender Systems. CoRR abs/2007.13019 (2020) - [i21]Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy:
ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks. CoRR abs/2009.14738 (2020) - [i20]Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy:
Bridging the Performance Gap between FGSM and PGD Adversarial Training. CoRR abs/2011.05157 (2020) - [i19]Sahithya Ravi, Samaneh Khoshrou, Mykola Pechenizkiy:
ViDi: Descriptive Visual Data Clustering as Radiologist Assistant in COVID-19 Streamline Diagnostic. CoRR abs/2011.14871 (2020) - [i18]Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy:
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders. CoRR abs/2012.00560 (2020)
2010 – 2019
- 2019
- [j31]Jianpeng Zhang, Kaijie Zhu, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy:
Cluster-preserving sampling from fully-dynamic streaming graphs. Inf. Sci. 482: 279-300 (2019) - [c116]Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy:
Joint role and community detection in networks via L2, 1 norm regularized nonnegative matrix tri-factorization. ASONAM 2019: 168-175 - [c115]Yulong Pei, Jianpeng Zhang, George H. L. Fletcher, Mykola Pechenizkiy:
Infinite motif stochastic blockmodel for role discovery in networks. ASONAM 2019: 456-459 - [c114]Samaneh Khoshrou, Mykola Pechenizkiy:
Adaptive Long-Term Ensemble Learning from Multiple High-Dimensional Time-Series. DS 2019: 511-521 - [c113]Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy:
Learning with delayed synaptic plasticity. GECCO 2019: 152-160 - [c112]Emilia Oikarinen, Kai Puolamäki, Samaneh Khoshrou, Mykola Pechenizkiy:
Supervised Human-Guided Data Exploration. PKDD/ECML Workshops (1) 2019: 85-101 - [c111]Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy:
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. RMSE@RecSys 2019 - [c110]Yuhao Wang, Vlado Menkovski, Ivan Wang Hei Ho, Mykola Pechenizkiy:
VANET Meets Deep Learning: The Effect of Packet Loss on the Object Detection Performance. VTC Spring 2019: 1-5 - [i17]Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy:
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware. CoRR abs/1901.09181 (2019) - [i16]Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy:
Intrinsically Sparse Long Short-Term Memory Networks. CoRR abs/1901.09208 (2019) - [i15]Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy:
Learning with Delayed Synaptic Plasticity. CoRR abs/1903.09393 (2019) - [i14]Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, Matt Coler, George H. L. Fletcher, Mykola Pechenizkiy:
Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions. CoRR abs/1904.01709 (2019) - [i13]Xin Du, Lei Sun, Wouter Duivesteijn, Alexander G. Nikolaev, Mykola Pechenizkiy:
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data. CoRR abs/1904.13335 (2019) - [i12]Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy:
On improving deep learning generalization with adaptive sparse connectivity. CoRR abs/1906.11626 (2019) - [i11]Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy:
A Human-Grounded Evaluation of SHAP for Alert Processing. CoRR abs/1907.03324 (2019) - [i10]Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy:
Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models. CoRR abs/1907.03334 (2019) - [i9]Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy:
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. CoRR abs/1908.00831 (2019) - [i8]Iftitahu Ni'mah, Vlado Menkovski, Mykola Pechenizkiy:
BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation. CoRR abs/1909.09485 (2019) - [i7]Masoud Mansoury, Himan Abdollahpouri, Joris Rombouts, Mykola Pechenizkiy:
The Relationship between the Consistency of Users' Ratings and Recommendation Calibration. CoRR abs/1911.00852 (2019) - 2018
- [j30]Rosa Sicilia, Stella Lo Giudice, Yulong Pei, Mykola Pechenizkiy, Paolo Soda:
Twitter rumour detection in the health domain. Expert Syst. Appl. 110: 33-40 (2018) - [j29]Jianpeng Zhang, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy:
A bounded-size clustering algorithm on fully-dynamic streaming graphs. Intell. Data Anal. 22(5): 1039-1058 (2018) - [j28]Negar Ahmadi, Rene M. H. Besseling, Mykola Pechenizkiy:
Assessment of visibility graph similarity as a synchronization measure for chaotic, noisy and stochastic time series. Soc. Netw. Anal. Min. 8(1): 47:1-47:17 (2018) - [j27]José María Luna, Francisco Padillo, Mykola Pechenizkiy, Sebastián Ventura:
Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data. IEEE Trans. Cybern. 48(10): 2851-2865 (2018) - [j26]José María Luna, Mykola Pechenizkiy, María José del Jesus, Sebastián Ventura:
Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming. IEEE Trans. Cybern. 48(11): 3030-3044 (2018) - [c109]Negar Ahmadi, Evelien Carrette, Albert P. Aldenkamp, Mykola Pechenizkiy:
Finding Predictive EEG Complexity Features for Classification of Epileptic and Psychogenic Nonepileptic Seizures Using Imperialist Competitive Algorithm. CBMS 2018: 164-169 - [c108]Xin Du, Wouter Duivesteijn, Mykola Pechenizkiy:
ELBA: Exceptional Learning Behavior Analysis. EDM 2018 - [c107]Anil Yaman, Giovanni Iacca, Matt Coler, George H. L. Fletcher, Mykola Pechenizkiy:
Multi-strategy Differential Evolution. EvoApplications 2018: 617-633 - [c106]Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy:
Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution. GECCO 2018: 569-576 - [c105]Yulong Pei, Jianpeng Zhang, George H. L. Fletcher, Mykola Pechenizkiy:
DyNMF: Role Analytics in Dynamic Social Networks. IJCAI 2018: 3818-3824 - [c104]Simon van der Zon, Wouter Duivesteijn, Werner van Ipenburg, Jan Veldsink, Mykola Pechenizkiy:
ICIE 1.0: A Novel Tool for Interactive Contextual Interaction Explanations. MIDAS/PAP@PKDD/ECML 2018: 81-94 - [c103]Wouter Ligtenberg, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy:
Tink: A Temporal Graph Analytics Library for Apache Flink. WWW (Companion Volume) 2018: 71-72 - [i6]Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy:
Limited Evaluation Cooperative Co-evolutionary Differential Evolution for Large-scale Neuroevolution. CoRR abs/1804.07234 (2018) - [i5]Yulong Pei, Xin Du, Jianpeng Zhang, George H. L. Fletcher, Mykola Pechenizkiy:
struc2gauss: Structure Preserving Network Embedding via Gaussian Embedding. CoRR abs/1805.10043 (2018) - [i4]Oren Zeev-Ben-Mordehai, Wouter Duivesteijn, Mykola Pechenizkiy:
Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally. CoRR abs/1808.07243 (2018) - [i3]Wenting Xiong, Iftitahu Ni'mah, Juan M. G. Huesca, Werner van Ipenburg, Jan Veldsink, Mykola Pechenizkiy:
Looking Deeper into Deep Learning Model: Attribution-based Explanations of TextCNN. CoRR abs/1811.03970 (2018) - 2017
- [j25]Elisa Costante, Jerry den Hartog, Milan Petkovic, Sandro Etalle, Mykola Pechenizkiy:
A white-box anomaly-based framework for database leakage detection. J. Inf. Secur. Appl. 32: 27-46 (2017) - [c102]Rosa Sicilia, Stella Lo Giudice, Yulong Pei, Mykola Pechenizkiy, Paolo Soda:
Health-related rumour detection on Twitter. BIBM 2017: 1599-1606 - [c101]Negar Ahmadi, Yulong Pei, Mykola Pechenizkiy:
Detection of Alcoholism Based on EEG Signals and Functional Brain Network Features Extraction. CBMS 2017: 179-184 - [c100]Jianpeng Zhang, Kaijie Zhu, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy:
Clustering-Structure Representative Sampling from Graph Streams. COMPLEX NETWORKS 2017: 265-277 - [c99]Roberto Martínez Maldonado, Kalina Yacef, Augusto Dias Pereira dos Santos, Simon Buckingham Shum, Vanessa Echeverría, Olga C. Santos, Mykola Pechenizkiy:
Towards Proximity Tracking and Sensemaking for Supporting Teamwork and Learning. ICALT 2017: 89-91 - [c98]Alexandr V. Maslov, Mykola Pechenizkiy, Yulong Pei, Indre Zliobaite, Alexander Shklyaev, Tommi Kärkkäinen, Jaakko Hollmén:
BLPA: Bayesian learn-predict-adjust method for online detection of recurrent changepoints. IJCNN 2017: 1916-1923 - [c97]Roberto Martínez Maldonado, Augusto Dias Pereira dos Santos, Vanessa Echeverría, Kalina Yacef, Mykola Pechenizkiy:
How to Capitalise on Mobility, Proximity and Motion Analytics to Support Formal and Informal Education? MMLA-CrossLAK@LAK 2017: 39-46 - [c96]Simon van der Zon, Oren Zeev-Ben-Mordehai, Tom Vrijdag, Werner van Ipenburg, Wouter Duivesteijn, Jan Veldsink, Mykola Pechenizkiy:
BoostEMM - Transparent Boosting using Exceptional Model Mining. MIDAS@PKDD/ECML 2017: 5-16 - [c95]Wouter Duivesteijn, Tara Farzami, Thijs Putman, Evertjan Peer, Hilde J. P. Weerts, Jasper N. Adegeest, Gerson Foks, Mykola Pechenizkiy:
Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining. ECML/PKDD (3) 2017: 114-126 - [c94]Roberto Martínez Maldonado, Mykola Pechenizkiy, Simon Buckingham Shum, Tamara Power, Carolyn Hayes, Carmen Axisa:
Modelling Embodied Mobility Teamwork Strategies in a Simulation-Based Healthcare Classroom. UMAP 2017: 308-312 - 2016
- [j24]Leonardo Onofri, Paolo Soda, Mykola Pechenizkiy, Giulio Iannello:
A survey on using domain and contextual knowledge for human activity recognition in video streams. Expert Syst. Appl. 63: 97-111 (2016) - [j23]José María Luna, Mykola Pechenizkiy, Sebastián Ventura:
Mining exceptional relationships with grammar-guided genetic programming. Knowl. Inf. Syst. 47(3): 571-594 (2016) - [j22]José María Luna, Alberto Cano, Mykola Pechenizkiy, Sebastián Ventura:
Speeding-Up Association Rule Mining With Inverted Index Compression. IEEE Trans. Cybern. 46(12): 3059-3072 (2016) - [j21]Peter Brusilovsky, Mike Sharples, Gustavo R. Alves, Tiffany Barnes, Sherry Y. Chen, Carol H. C. Chu, Hendrik Drachsler, Seiji Isotani, Euan Lindsay, Xavier Ochoa, Mykola Pechenizkiy, Ma. Mercedes T. Rodrigo, Cristóbal Romero, Sergey A. Sosnovsky, Stefaan Ternier, Katrien Verbert:
Editorial: A Message from the Editorial Team and an Introduction to the January-March 2016 Issue. IEEE Trans. Learn. Technol. 9(1): 1-4 (2016) - [c93]Jianpeng Zhang, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy:
Structural measures of clustering quality on graph samples. ASONAM 2016: 345-348 - [c92]Negar Ahmadi, Mykola Pechenizkiy:
Application of Horizontal Visibility Graph as a Robust Measure of Neurophysiological Signals Synchrony. CBMS 2016: 273-278 - [c91]Alejandro Montes García, Natalia Stash, Marc Fabri, Paul De Bra, George H. L. Fletcher, Mykola Pechenizkiy:
Adaptive web-based educational application for autistic students. HT (Extended Proceedings) 2016 - [c90]Harm Eggels, Ruud van Elk, Mykola Pechenizkiy:
Explaining Soccer Match Outcomes with Goal Scoring Opportunities Predictive Analytics. MLSA@PKDD/ECML 2016 - [c89]Alexander Nieuwenhuijse, Jorn Bakker, Mykola Pechenizkiy:
Finding Incident-Related Social Media Messages for Emergency Awareness. ECML/PKDD (3) 2016: 67-70 - [c88]Jianpeng Zhang, Mykola Pechenizkiy, Yulong Pei, Julia Efremova:
A robust density-based clustering algorithm for multi-manifold structure. SAC 2016: 832-838 - [c87]Wouter van Heeswijk, George H. L. Fletcher, Mykola Pechenizkiy:
On structure preserving sampling and approximate partitioning of graphs. SAC 2016: 875-882 - [c86]Alexandr V. Maslov, Hoang Thanh Lam, Mykola Pechenizkiy, Eric Bouillet, Tommi Kärkkäinen:
DOBRO: a prediction error correcting robot under drifts. SAC 2016: 945-948 - [c85]Alexandr V. Maslov, Mykola Pechenizkiy, Indre Zliobaite, Tommi Kärkkäinen:
Modelling Recurrent Events for Improving Online Change Detection. SDM 2016: 549-557 - [c84]Alejandro Montes García, Natalia Stash, Marc Fabri, Paul De Bra, George H. L. Fletcher, Mykola Pechenizkiy:
WiBAF into a CMS: Personalization in Learning Environments Made Easy. UMAP (Extended Proceedings) 2016 - 2015
- [c83]Sergey Chernov, Mykola Pechenizkiy, Tapani Ristaniemi:
The influence of dataset size on the performance of cell outage detection approach in LTE-A networks. ICICS 2015: 1-5 - [c82]Georgios Aravanis, Anca I. D. Bucur, Mykola Pechenizkiy:
Hippocrates: A Context-Aware, Collaboration Enabling Search Tool. CBMS 2015: 320-325 - [c81]Dragan Gasevic, Taylor Martin, Zachary A. Pardos, Mykola Pechenizkiy, John C. Stamper, Osmar R. Zaïane:
Ethics and Privacy in EDM. EDM 2015: 13 - [c80]Ryan S. Baker, Peter Brusilovsky, Dragan Gasevic, Neil T. Heffernan, Mykola Pechenizkiy, Alyssa Friend Wise:
Grand Challenges for EDM and Related Research Areas. EDM 2015: 15 - [c79]Mykola Pechenizkiy:
Predictive analytics on evolving data streams anticipating and adapting to changes in known and unknown contexts. HPCS 2015: 658-659 - [p4]Erik Tromp, Mykola Pechenizkiy:
Pattern-Based Emotion Classification on Social Media. Advances in Social Media Analysis 2015: 1-20 - [e7]Olga C. Santos, Jesus Boticario, Cristóbal Romero, Mykola Pechenizkiy, Agathe Merceron, Piotr Mitros, José María Luna, Marian Cristian Mihaescu, Pablo Moreno, Arnon Hershkovitz, Sebastián Ventura, Michel C. Desmarais:
Proceedings of the 8th International Conference on Educational Data Mining, EDM 2015, Madrid, Spain, June 26-29, 2015. International Educational Data Mining Society (IEDMS) 2015, ISBN 978-8-4606-9425-0 [contents] - 2014
- [j20]João Gama, Indre Zliobaite, Albert Bifet, Mykola Pechenizkiy, Abdelhamid Bouchachia:
A survey on concept drift adaptation. ACM Comput. Surv. 46(4): 44:1-44:37 (2014) - [j19]R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aalst, Indre Zliobaite, Mykola Pechenizkiy:
Dealing With Concept Drifts in Process Mining. IEEE Trans. Neural Networks Learn. Syst. 25(1): 154-171 (2014) - [c78]Hindra Kurniawan, Mykola Pechenizkiy:
Towards the Stress Analytics Framework: Managing, Mining, and Visualizing Multi-modal Data for Stress Awareness. CBMS 2014: 541-542 - [c77]Elisa Costante, Jerry den Hartog, Milan Petkovic, Sandro Etalle, Mykola Pechenizkiy:
Hunting the Unknown - White-Box Database Leakage Detection. DBSec 2014: 243-259 - [c76]Mykola Pechenizkiy, Pedro A. Toledo:
Learning to Teach like a Bandit. EDM 2014: 381-382 - [c75]Alejandro Montes García, Paul De Bra, George H. L. Fletcher, Mykola Pechenizkiy:
A DSL based on CSS for hypertext adaptation. HT 2014: 313-315 - [c74]Julia Kiseleva, Alejandro Montes García, Yongming Luo, Mykola Pechenizkiy, Paul De Bra, Jaap Kamps:
Applying Learning to Rank Techniques to Contextual Suggestions. TREC 2014 - [i2]Erik Tromp, Mykola Pechenizkiy:
Rule-based Emotion Detection on Social Media: Putting Tweets on Plutchik's Wheel. CoRR abs/1412.4682 (2014) - 2013
- [j18]Minseok Song, H. Yang, Seyed Hossein Siadat, Mykola Pechenizkiy:
A comparative study of dimensionality reduction techniques to enhance trace clustering performances. Expert Syst. Appl. 40(9): 3722-3737 (2013) - [j17]Mykola Pechenizkiy, Indre Zliobaite:
Introduction to the special issue on handling concept drift in adaptive information systems. Evol. Syst. 4(1): 1-2 (2013) - [j16]