Mykola Pechenizkiy

429 papers A* 34A 19B 64C 11Misc 8Journal 196Unranked 82

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Feature Selection via Dynamic Feature Graph. IEEE Trans. Knowl. Data Eng. Chenchen Wang, Mykola Pechenizkiy, Jinmao Wei, Jian Liu
2026	J	`jnl`	Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information. CoRR Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet, Russel Pears
2026	A*	`conf`	Investigating Social Bias Propagation in Federated Fine-tuning of Large Language Models. AAAI Jiaxu Zhao, Meng Fang, Mingze Zhong, Shunfeng Zheng, Ling Chen, Mykola Pechenizkiy
2026	—	`conf`	MATH-IDN: A Multilingual Mathematical Problem Solving Dataset Featuring Local Languages in Indonesia. EACL (Findings) Xiao Xiao, Iftitahu Ni'mah, Yuyun Wabula, Mykola Pechenizkiy, Meng Fang
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IX ECML/PKDD (9) Inês Dutra, Mykola Pechenizkiy, Paulo Cortez, Sepideh Pashami, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track and Demo Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part X ECML/PKDD (10) Inês Dutra, Mykola Pechenizkiy, Paulo Cortez, Sepideh Pashami, Arian Pasquali, Nuno Moniz, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	—	`ed.`	Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VIII ECML/PKDD (8) Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Rita P. Ribeiro, Inês Dutra, Mykola Pechenizkiy, Paulo Cortez, Sepideh Pashami, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama
2026	J	`jnl`	One Model for All: Multi-Objective Controllable Language Models. Trans. Mach. Learn. Res. Qiang He, Yucheng Yang, Tianyi Zhou, Meng Fang, Mykola Pechenizkiy, Setareh Maghsudi
2026	J	`jnl`	PhysVid: Physics Aware Local Conditioning for Generative Video Models. CoRR Saurabh Pathak, Elahe Arani, Mykola Pechenizkiy, Bahram Zonooz
2026	J	`jnl`	SafeTutors: Benchmarking Pedagogical Safety in AI Tutoring Systems. CoRR Rima Hazra, Bikram Ghuku, Ilona Marchenko, Yaroslava Tokarieva, Sayan Layek, Somnath Banerjee, Julia Stoyanovich, Mykola Pechenizkiy
2026	J	`jnl`	The Unfairness of Multifactorial Bias in Recommendation. CoRR Masoud Mansoury, Jin Huang, Mykola Pechenizkiy, Herke van Hoof, Maarten de Rijke
2025	J	`jnl`	A simple contrastive embedding framework for low-resource fake news detection. Neural Comput. Appl. Iftitahu Ni'mah, Rini Wijayanti, Agung Santosa, Asril Jarin, Tri Sampurno, Mohammad Teduh Uliniansyah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2025	J	`jnl`	Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity. CoRR Qiao Xiao, Boqian Wu, Andrey Poddubnyy, Elena Mocanu, Phuong H. Nguyen, Mykola Pechenizkiy, Decebal Constantin Mocanu
2025	—	`conf`	Benchmarking Foundation Models with Retrieval-Augmented Generation in Olympic-Level Physics Problem Solving. EMNLP (Findings) Shunfeng Zheng, Yudi Zhang, Meng Fang, Zihan Zhang, Zhitan Wu, Mykola Pechenizkiy, Ling Chen
2025	J	`jnl`	Benchmarking Foundation Models with Retrieval-Augmented Generation in Olympic-Level Physics Problem Solving. CoRR Shunfeng Zheng, Yudi Zhang, Meng Fang, Zihan Zhang, Zhitan Wu, Mykola Pechenizkiy, Ling Chen
2025	A*	`conf`	Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles. ICDM Xin Du, Subramanian Ramamoorthy, Wouter Duivesteijn, Jin Tian, Mykola Pechenizkiy
2025	A	`conf`	Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity. AAMAS Calarina Muslimani, Bram Grooten, Deepak Ranganatha Sastry Mamillapalli, Mykola Pechenizkiy, Decebal Constantin Mocanu, Matthew E. Taylor
2025	—	`conf`	Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well. ECML/PKDD (3) Xin Du, Sikun Yang, Wouter Duivesteijn, Mykola Pechenizkiy
2025	J	`jnl`	Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well. CoRR Xin Du, Sikun Yang, Wouter Duivesteijn, Mykola Pechenizkiy
2025	J	`jnl`	Counterfactual Explanations for Time Series Should be Human-Centered and Temporally Coherent in Interventions. CoRR Emmanuel C. Chukwu, Rianne Margaretha Schouten, Monique Tabak, Mykola Pechenizkiy
2025	J	`jnl`	Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones? CoRR Yudi Zhang, Lu Wang, Meng Fang, Yali Du, Chenghua Huang, Jun Wang, Qingwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
2025	A*	`conf`	Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness. ICLR Boqian Wu, Qiao Xiao, Shunxin Wang, Nicola Strisciuglio, Mykola Pechenizkiy, Maurice van Keulen, Decebal Constantin Mocanu, Elena Mocanu
2025	C	`conf`	Energy Consumption Prediction with Uncertainty Quantification for Electric Truck Operations: A Data-Driven Approach. VEHITS Rik Litjens, Róbinson Medina, Nikos Avramis, Camiel Beckers, S. Steven Wilkins, Mykola Pechenizkiy
2025	—	`ed.`	European Workshop on Algorithmic Fairness, 30-2 July 2025, Eindhoven University of Technology, Eindhoven, The Netherlands. EWAF Hilde J. P. Weerts, Mykola Pechenizkiy, Doris Allhutter, Ana Maria Corrêa, Thomas Grote, Cynthia C. S. Liem
2025	J	`jnl`	FS-GNN: Improving Fairness in Graph Neural Networks via Joint Sparsification. Neurocomputing Jiaxu Zhao, Tianjin Huang, Shiwei Liu, Jie Yin, Yulong Pei, Meng Fang, Mykola Pechenizkiy
2025	—	`conf`	Fourth European Workshop on Algorithmic Fairness (EWAF'25). EWAF Hilde J. P. Weerts, Mykola Pechenizkiy, Doris Allhutter, Ana Maria Corrêa, Thomas Grote, Cynthia C. S. Liem
2025	A	`conf`	From Benchmarking to Understanding FairML. ECAI Mykola Pechenizkiy, Hilde J. P. Weerts, Cassio de Campos, Yuya Sasaki, Julia Stoyanovich
2025	A*	`conf`	HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents. ICLR Tristan Tomilin, Meng Fang, Mykola Pechenizkiy
2025	J	`jnl`	HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents. CoRR Tristan Tomilin, Meng Fang, Mykola Pechenizkiy
2025	J	`jnl`	Introduction to The Special Section on Safe AI. SIGKDD Explor. Mykola Pechenizkiy, Stiven S. Dias
2025	J	`jnl`	Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution. CoRR Qiao Xiao, Alan Ansell, Boqian Wu, Lu Yin, Mykola Pechenizkiy, Shiwei Liu, Decebal Constantin Mocanu
2025	J	`jnl`	MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning. CoRR Tristan Tomilin, Luka van den Boogaard, Samuel Garcin, Bram Grooten, Meng Fang, Mykola Pechenizkiy
2025	J	`jnl`	MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages. CoRR Wenhan Han, Yifan Zhang, Zhixun Chen, Binbin Li, Haobin Lin, Bingni Zhang, Taifeng Wang, Mykola Pechenizkiy, Meng Fang, Yin Zheng
2025	J	`jnl`	NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling. CoRR Bram Grooten, Farid Hasanov, Chenxiang Zhang, Qiao Xiao, Boqian Wu, Zahra Atashgahi, Ghada Sokar, Shiwei Liu, Lu Yin, Elena Mocanu, Mykola Pechenizkiy, Decebal Constantin Mocanu
2025	J	`jnl`	On Adversarial Robustness of Language Models in Transfer Learning. CoRR Bohdan Turbal, Anastasiia Mazur, Jiaxu Zhao, Mykola Pechenizkiy
2025	C	`conf`	PillagerBench: Benchmarking LLM-Based Agents in Competitive Minecraft Team Environments. CoG Olivier Schipper, Yudi Zhang, Yali Du, Mykola Pechenizkiy, Meng Fang
2025	J	`jnl`	PillagerBench: Benchmarking LLM-Based Agents in Competitive Minecraft Team Environments. CoRR Olivier Schipper, Yudi Zhang, Yali Du, Mykola Pechenizkiy, Meng Fang
2025	A*	`conf`	Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization. ICML Yucheng Yang, Tianyi Zhou, Mykola Pechenizkiy, Meng Fang
2025	J	`jnl`	ProSocialAlign: Preference Conditioned Test Time Alignment in Language Models. CoRR Somnath Banerjee, Sayan Layek, Sayantan Adak, Mykola Pechenizkiy, Animesh Mukherjee, Rima Hazra
2025	—	`ed.`	Proceedings of the 3rd European Workshop on Algorithmic Fairness, Mainz, Germany, July 1st to 3rd, 2024. EWAF Mattia Cerrato, Alesia Vallenas Coronel, Petra Ahrweiler, Michele Loi, Mykola Pechenizkiy, Aurelia Tamò-Larrieux
2025	J	`jnl`	REOBench: Benchmarking Robustness of Earth Observation Foundation Models. CoRR Xiang Li, Yong Tao, Siyuan Zhang, Siwei Liu, Zhitong Xiong, Chunbo Luo, Lu Liu, Mykola Pechenizkiy, Xiao Xiang Zhu, Tianjin Huang
2025	J	`jnl`	Rethinking Knowledge Transfer in Learning Using Privileged Information. Trans. Mach. Learn. Res. Danil Provodin, Bram van den Akker, Christina Katsimerou, Maurits Clemens Kaptein, Mykola Pechenizkiy
2025	A*	`conf`	RuAG: Learned-rule-augmented Generation for Large Language Models. ICLR Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
2025	J	`jnl`	Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning. CoRR Yucheng Yang, Tianyi Zhou, Qiang He, Lei Han, Mykola Pechenizkiy, Meng Fang
2025	—	`conf`	Understanding Large Language Model Vulnerabilities to Social Bias Attacks. ACL (1) Jiaxu Zhao, Meng Fang, Fanghua Ye, Ke Xu, Qin Zhang, Joey Tianyi Zhou, Mykola Pechenizkiy
2025	—	`conf`	Unmasking Style Sensitivity: A Causal Analysis of Bias Evaluation Instability in Large Language Models. ACL (1) Jiaxu Zhao, Meng Fang, Kun Zhang, Mykola Pechenizkiy
2025	A*	`conf`	Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. AAAI Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
2024	J	`jnl`	(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork. CoRR Tianjin Huang, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Shiwei Liu, Tianlong Chen
2024	J	`jnl`	A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams. CoRR Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet
2024	—	`conf`	A Structural-Clustering Based Active Learning for Graph Neural Networks. IDA (1) Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy
2024	—	`conf`	Adaptive Sparsity Level During Training for Efficient Time Series Forecasting with Transformers. ECML/PKDD (1) Zahra Atashgahi, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
2024	A	`conf`	Are Sparse Neural Networks Better Hard Sample Learners? BMVC Qiao Xiao, Boqian Wu, Lu Yin, Christopher Neil Gadzinski, Tianjin Huang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2024	J	`jnl`	Are Sparse Neural Networks Better Hard Sample Learners? CoRR Qiao Xiao, Boqian Wu, Lu Yin, Christopher Neil Gadzinski, Tianjin Huang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2024	A	`conf`	Automatic Curriculum for Unsupervised Reinforcement Learning. AAMAS Yucheng Yang, Tianyi Zhou, Lei Han, Meng Fang, Mykola Pechenizkiy
2024	J	`jnl`	Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity. CoRR Calarina Muslimani, Bram Grooten, Deepak Ranganatha Sastry Mamillapalli, Mykola Pechenizkiy, Decebal Constantin Mocanu, Matthew E. Taylor
2024	—	`conf`	CHAmbi: A New Benchmark on Chinese Ambiguity Challenges for Large Language Models. EMNLP (Findings) Qin Zhang, Sihan Cai, Jiaxu Zhao, Mykola Pechenizkiy, Meng Fang
2024	J	`jnl`	Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. J. Artif. Intell. Res. Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter
2024	A	`conf`	Dynamic Data Pruning for Automatic Speech Recognition. INTERSPEECH Qiao Xiao, Pingchuan Ma, Adriana Fernandez-Lopez, Boqian Wu, Lu Yin, Stavros Petridis, Mykola Pechenizkiy, Maja Pantic, Decebal Constantin Mocanu, Shiwei Liu
2024	J	`jnl`	Dynamic Data Pruning for Automatic Speech Recognition. CoRR Qiao Xiao, Pingchuan Ma, Adriana Fernandez-Lopez, Boqian Wu, Lu Yin, Stavros Petridis, Mykola Pechenizkiy, Maja Pantic, Decebal Constantin Mocanu, Shiwei Liu
2024	J	`jnl`	Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness. CoRR Boqian Wu, Qiao Xiao, Shunxin Wang, Nicola Strisciuglio, Mykola Pechenizkiy, Maurice van Keulen, Decebal Constantin Mocanu, Elena Mocanu
2024	A*	`conf`	E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. NeurIPS Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu
2024	A*	`conf`	Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling. ICML Danil Provodin, Maurits Clemens Kaptein, Mykola Pechenizkiy
2024	J	`jnl`	Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling. CoRR Danil Provodin, Maurits Kaptein, Mykola Pechenizkiy
2024	J	`jnl`	Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data. CoRR Rik Raes, Saskia Lensink, Mykola Pechenizkiy
2024	—	`conf`	Exceptional Subitizing Patterns: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression. ECML/PKDD (10) Rianne Margaretha Schouten, Wouter Duivesteijn, Pekka Räsänen, Jacob M. Paul, Mykola Pechenizkiy
2024	J	`jnl`	FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering. Expert Syst. Appl. Ricky Maulana Fajri, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
2024	J	`jnl`	FairSNA: Algorithmic Fairness in Social Network Analysis. ACM Comput. Surv. Akrati Saxena, George Fletcher, Mykola Pechenizkiy
2024	A*	`conf`	Large Language Models Are Neurosymbolic Reasoners. AAAI Meng Fang, Shilong Deng, Yudi Zhang, Zijing Shi, Ling Chen, Mykola Pechenizkiy, Jun Wang
2024	J	`jnl`	Large Language Models Are Neurosymbolic Reasoners. CoRR Meng Fang, Shilong Deng, Yudi Zhang, Zijing Shi, Ling Chen, Mykola Pechenizkiy, Jun Wang
2024	J	`jnl`	Learning Efficient and Fair Policies for Uncertainty-Aware Collaborative Human-Robot Order Picking. CoRR Igor G. Smit, Zaharah Allah Bukhsh, Mykola Pechenizkiy, Kostas Alogariastos, Kasper Hendriks, Yingqian Zhang
2024	A	`conf`	MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. AAMAS Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2024	—	`conf`	MedINST: Meta Dataset of Biomedical Instructions. EMNLP (Findings) Wenhan Han, Meng Fang, Zihan Zhang, Yu Yin, Zirui Song, Ling Chen, Mykola Pechenizkiy, Qingyu Chen
2024	J	`jnl`	MedINST: Meta Dataset of Biomedical Instructions. CoRR Wenhan Han, Meng Fang, Zihan Zhang, Yu Yin, Zirui Song, Ling Chen, Mykola Pechenizkiy, Qingyu Chen
2024	—	`conf`	More than Minorities and Majorities: Understanding Multilateral Bias in Language Generation. ACL (Findings) Jiaxu Zhao, Zijing Shi, Yitong Li, Yulong Pei, Ling Chen, Meng Fang, Mykola Pechenizkiy
2024	J	`jnl`	Nerva: a Truly Sparse Implementation of Neural Networks. CoRR Wieger Wesselink, Bram Grooten, Qiao Xiao, Cassio de Campos, Mykola Pechenizkiy
2024	J	`jnl`	One-Shot Federated Learning with Bayesian Pseudocoresets. CoRR Tim D'Hondt, Mykola Pechenizkiy, Robert Peharz
2024	A*	`conf`	Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. ICML Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu
2024	—	`ch.`	RATE-Analytics: Next Generation Predictive Analytics for Data-Driven Banking and Insurance. Commit2Data Dennis Collaris, Mykola Pechenizkiy, Jarke J. van Wijk
2024	J	`jnl`	Rethinking Knowledge Transfer in Learning Using Privileged Information. CoRR Danil Provodin, Bram van den Akker, Christina Katsimerou, Maurits Kaptein, Mykola Pechenizkiy
2024	J	`jnl`	Robust Active Learning (RoAL): Countering Dynamic Adversaries in Active Learning with Elastic Weight Consolidation. CoRR Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy
2024	J	`jnl`	RuAG: Learned-rule-augmented Generation for Large Language Models. CoRR Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
2024	—	`conf`	Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and Predictive Bias. ECML/PKDD (8) Adam Dubowski, Hilde J. P. Weerts, Anouk Wolters, Mykola Pechenizkiy
2024	A	`conf`	Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks. AISTATS Kaiting Liu, Zahra Atashgahi, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu
2024	A*	`conf`	Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning. ICLR Yucheng Yang, Tianyi Zhou, Qiang He, Lei Han, Mykola Pechenizkiy, Meng Fang
2024	—	`conf`	The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action. FAccT Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
2024	J	`jnl`	The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action. CoRR Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
2024	A	`conf`	Unveiling the Power of Sparse Neural Networks for Feature Selection. ECAI Zahra Atashgahi, Tennison Liu, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu, Mihaela van der Schaar
2024	J	`jnl`	Unveiling the Power of Sparse Neural Networks for Feature Selection. CoRR Zahra Atashgahi, Tennison Liu, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu, Mihaela van der Schaar
2023	J	`jnl`	A Structural-Clustering Based Active Learning for Graph Neural Networks. CoRR Ricky Maulana Fajri, Yulong Pei, Lu Yin, Mykola Pechenizkiy
2023	J	`jnl`	Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers. CoRR Zahra Atashgahi, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
2023	—	`conf`	Algorithmic Unfairness Through the Lens of EU Non-Discrimination Law. EWAF Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
2023	—	`conf`	Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree. FAccT Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
2023	J	`jnl`	Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree. CoRR Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
2023	J	`jnl`	An AI-empowered infrastructure for risk prevention during medical examination. Expert Syst. Appl. Syed Ihtesham Hussain Shah, Muddasar Naeem, Giovanni Paragliola, Antonio Coronato, Mykola Pechenizkiy
2023	A*	`conf`	Are Large Kernels Better Teachers than Transformers for ConvNets? ICML Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
2023	J	`jnl`	Are Large Kernels Better Teachers than Transformers for ConvNets? CoRR Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
2023	A	`conf`	Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. AAMAS Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu
2023	J	`jnl`	Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. CoRR Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu
2023	—	`conf`	CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models. ACL (1) Jiaxu Zhao, Meng Fang, Zijing Shi, Yitong Li, Ling Chen, Mykola Pechenizkiy
2023	J	`jnl`	CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models. CoRR Jiaxu Zhao, Meng Fang, Zijing Shi, Yitong Li, Ling Chen, Mykola Pechenizkiy
2023	A*	`conf`	COOM: A Game Benchmark for Continual Reinforcement Learning. NeurIPS Tristan Tomilin, Meng Fang, Yudi Zhang, Mykola Pechenizkiy
2023	J	`jnl`	Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. CoRR Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter
2023	J	`jnl`	Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams. ACM Trans. Knowl. Discov. Data Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet
2023	A*	`conf`	Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
2023	J	`jnl`	Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
2023	J	`jnl`	E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation. CoRR Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice van Keulen, Elena Mocanu
2023	—	`conf`	Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
2023	J	`jnl`	Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
2023	A*	`conf`	FALL: A Modular Adaptive Learning Platform for Streaming Data. ICDE Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet
2023	J	`jnl`	Fairness-aware fake news mitigation using counter information propagation. Appl. Intell. Akrati Saxena, Cristina Gutiérrez Bierbooms, Mykola Pechenizkiy
2023	J	`jnl`	GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models. CoRR Jiaxu Zhao, Meng Fang, Shirui Pan, Wenpeng Yin, Mykola Pechenizkiy
2023	J	`jnl`	GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning. CoRR Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy
2023	—	`conf`	Heterophily-Based Graph Neural Network for Imbalanced Classification. COMPLEX NETWORKS (1) Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
2023	J	`jnl`	Heterophily-Based Graph Neural Network for Imbalanced Classification. CoRR Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
2023	—	`conf`	Improving Recommender System Diversity with Variational Autoencoders. BIAS Sheetal Borar, Hilde J. P. Weerts, Binyam Gebre, Mykola Pechenizkiy
2023	A*	`conf`	Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach. NeurIPS Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy
2023	J	`jnl`	KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-Answering. CoRR Iftitahu Ni'mah, Samaneh Khoshrou, Vlado Menkovski, Mykola Pechenizkiy
2023	B	`conf`	LEMON: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models. IDA Dennis Collaris, Pratik Gajane, Joost Jorritsma, Jarke J. van Wijk, Mykola Pechenizkiy
2023	A*	`conf`	Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
2023	J	`jnl`	MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. CoRR Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2023	A*	`conf`	More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
2023	—	`conf`	NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. ACL (1) Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2023	J	`jnl`	NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. CoRR Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2023	J	`jnl`	Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. CoRR Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu
2023	B	`ed.`	Proceedings of the 16th International Conference on Educational Data Mining, EDM 2023, Bengaluru, India, July 11-14, 2023 EDM Mingyu Feng, Tanja Käser, Partha P. Talukdar, Rakesh Agrawal, Y. Narahari, Mykola Pechenizkiy
2023	J	`jnl`	Provably Efficient Exploration in Constrained Reinforcement Learning: Posterior Sampling Is All You Need. CoRR Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
2023	—	`conf`	REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training. ECML/PKDD (2) Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy
2023	J	`jnl`	REST: Enhancing Group Robustness in DNNs through Reweighted Sparse Training. CoRR Jiaxu Zhao, Lu Yin, Shiwei Liu, Meng Fang, Mykola Pechenizkiy
2023	J	`jnl`	Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. CoRR Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
2023	J	`jnl`	Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. Trans. Mach. Learn. Res. Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu
2023	J	`jnl`	Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
2022	J	`jnl`	A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems. ACM Trans. Inf. Syst. Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2022	B	`conf`	A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams. DSAA Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet
2022	J	`jnl`	A brain-inspired algorithm for training highly sparse neural networks. Mach. Learn. Zahra Atashgahi, Joost Pieterse, Shiwei Liu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
2022	J	`jnl`	An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning. CoRR Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
2022	J	`jnl`	Analyzing and repairing concept drift adaptation in data stream classification. Mach. Learn. Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson
2022	—	`conf`	Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks. ECML/PKDD (3) Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
2022	Misc	`conf`	Characterizing Data Scientists' Mental Models of Local Feature Importance. NordiCHI Dennis Collaris, Hilde J. P. Weerts, Daphne Miedema, Jarke J. van Wijk, Mykola Pechenizkiy
2022	A*	`conf`	Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. ICLR Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2022	J	`jnl`	Direction-aggregated Attack for Transferable Adversarial Examples. ACM J. Emerg. Technol. Comput. Syst. Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
2022	J	`jnl`	Does the End Justify the Means? On the Moral Justification of Fairness-Aware Machine Learning. CoRR Hilde J. P. Weerts, Lambèr Royakkers, Mykola Pechenizkiy
2022	A*	`conf`	Dynamic Sparse Network for Time Series Classification: Learning What to "See". NeurIPS Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu
2022	J	`jnl`	Dynamic Sparse Network for Time Series Classification: Learning What to "see". CoRR Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu
2022	A*	`conf`	Dynamic Sparse Training for Deep Reinforcement Learning. IJCAI Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone
2022	A	`conf`	Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS). SDM Rianne Margaretha Schouten, Wouter Duivesteijn, Mykola Pechenizkiy
2022	J	`jnl`	FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering. CoRR Ricky Maulana Fajri, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
2022	B	`conf`	FATED 2022: Fairness, Accountability, and Transparency in Educational Data. EDM Collin F. Lynch, Mirko Marras, Mykola Pechenizkiy, Anna N. Rafferty, Steven Ritter, Vinitra Swamy, Renzhe Yu
2022	J	`jnl`	FairSNA: Algorithmic Fairness in Social Network Analysis. CoRR Akrati Saxena, George Fletcher, Mykola Pechenizkiy
2022	J	`jnl`	HM-EIICT: Fairness-aware link prediction in complex networks using community information. J. Comb. Optim. Akrati Saxena, George Fletcher, Mykola Pechenizkiy
2022	—	`conf`	Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks. ECML/PKDD (1) Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2022	B	`conf`	Individual Fairness Evaluation for Automated Essay Scoring System. EDM Afrizal Doewes, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
2022	J	`jnl`	Introduction to the Special Section on AI in Manufacturing: Current Trends and Challenges. SIGKDD Explor. Jefrey Lijffijt, Dimitra Gkorou, Pieter Van Hertum, Alexander Ypma, Mykola Pechenizkiy, Joaquin Vanschoren
2022	C	`conf`	LevDoom: A Benchmark for Generalization on Level Difficulty in Reinforcement Learning. CoG Tristan Tomilin, Tianhong Dai, Meng Fang, Mykola Pechenizkiy
2022	J	`jnl`	Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
2022	J	`jnl`	Memory-free Online Change-point Detection: A Novel Neural Network Approach. CoRR Zahra Atashgahi, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
2022	J	`jnl`	Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions. Data Min. Knowl. Discov. Rianne Margaretha Schouten, Marcos L. P. Bueno, Wouter Duivesteijn, Mykola Pechenizkiy
2022	J	`jnl`	Mining trading patterns of pyramid schemes from financial time series data. Future Gener. Comput. Syst. Fang Lv, Wei Wang, Linxuan Han, Di Wang, Yulong Pei, Junheng Huang, Bailing Wang, Mykola Pechenizkiy
2022	J	`jnl`	More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. CoRR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang
2022	J	`jnl`	NodeSim: node similarity based network embedding for diverse link prediction. EPJ Data Sci. Akrati Saxena, George Fletcher, Mykola Pechenizkiy
2022	—	`conf`	Phrase-level Textual Adversarial Attack with Label Preservation. NAACL-HLT (Findings) Yibin Lei, Yu Cao, Dianqi Li, Tianyi Zhou, Meng Fang, Mykola Pechenizkiy
2022	J	`jnl`	Phrase-level Textual Adversarial Attack with Label Preservation. CoRR Yibin Lei, Yu Cao, Dianqi Li, Tianyi Zhou, Meng Fang, Mykola Pechenizkiy
2022	J	`jnl`	Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders. Mach. Learn. Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
2022	J	`jnl`	ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks. Mach. Learn. Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
2022	B	`conf`	Semantic-Based Few-Shot Classification by Psychometric Learning. IDA Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2022	J	`jnl`	Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu
2022	A	`conf`	Superposing many tickets into one: A performance booster for sparse neural network training. UAI Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy
2022	J	`jnl`	Survey on Fair Reinforcement Learning: Theory and Practice. CoRR Pratik Gajane, Akrati Saxena, Maryam Tavakol, George Fletcher, Mykola Pechenizkiy
2022	A*	`conf`	The Impact of Batch Learning in Stochastic Linear Bandits. ICDM Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
2022	J	`jnl`	The Impact of Batch Learning in Stochastic Linear Bandits. CoRR Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
2022	A*	`conf`	The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. ICLR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
2022	J	`jnl`	The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. CoRR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
2022	A*	`conf`	Where to Pay Attention in Sparse Training for Feature Selection? NeurIPS Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu
2022	J	`jnl`	Where to Pay Attention in Sparse Training for Feature Selection? CoRR Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu
2022	—	`conf`	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
2022	J	`jnl`	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
2021	J	`jnl`	A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems. CoRR Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2021	J	`jnl`	Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning. CoRR Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	J	`jnl`	Adversarial balancing-based representation learning for causal effect inference with observational data. Data Min. Knowl. Discov. Xin Du, Lei Sun, Wouter Duivesteijn, Alexander G. Nikolaev, Mykola Pechenizkiy
2021	B	`conf`	Analyzing and Repairing Concept Drift Adaptation in Data Stream Classification. DSAA Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson
2021	J	`jnl`	Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles. CoRR Xin Du, Subramanian Ramamoorthy, Wouter Duivesteijn, Jin Tian, Mykola Pechenizkiy
2021	J	`jnl`	Calibrated Adversarial Training. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2021	J	`jnl`	Direction-Aggregated Attack for Transferable Adversarial Examples. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
2021	A*	`conf`	Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. ICML Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	J	`jnl`	Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training. CoRR Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	J	`jnl`	Dynamic Sparse Training for Deep Reinforcement Learning. CoRR Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone
2021	J	`jnl`	Efficient and effective training of sparse recurrent neural networks. Neural Comput. Appl. Shiwei Liu, Iftitahu Ni'mah, Vlado Menkovski, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	J	`jnl`	Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions. Evol. Comput. Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, Matt Coler, George Fletcher, Mykola Pechenizkiy
2021	A*	`conf`	Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information. ICDE Ben Halstead, Yun Sing Koh, Patricia Riddle, Mykola Pechenizkiy, Albert Bifet, Russel Pears
2021	J	`jnl`	FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. CoRR Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2021	C	`conf`	Hierarchical Semantic Segmentation using Psychometric Learning. ACML Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
2021	J	`jnl`	Hierarchical Semantic Segmentation using Psychometric Learning. CoRR Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
2021	J	`jnl`	Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks. CoRR Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	How Fair is Fairness-aware Representative Ranking and Methods for Fair Ranking. CoRR Akrati Saxena, George Fletcher, Mykola Pechenizkiy
2021	—	`conf`	How Fair is Fairness-aware Representative Ranking? WWW (Companion Volume) Akrati Saxena, George Fletcher, Mykola Pechenizkiy
2021	J	`jnl`	Introduction to The Special Section on Bias and Fairness in AI. SIGKDD Explor. Toon Calders, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Salvatore Ruggieri
2021	J	`jnl`	Learning Invariant Representation for Continual Learning. CoRR Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	—	`ed.`	Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I PKDD/ECML Workshops (1) Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021	—	`ed.`	Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II PKDD/ECML Workshops (2) Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021	J	`jnl`	NodeSim: Node Similarity based Network Embedding for Diverse Link Prediction. CoRR Akrati Saxena, George Fletcher, Mykola Pechenizkiy
2021	—	`conf`	On Generalization of Graph Autoencoders with Adversarial Training. ECML/PKDD (2) Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	On Generalization of Graph Autoencoders with Adversarial Training. CoRR Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	B	`conf`	On the Limitations of Human-Computer Agreement in Automated Essay Scoring. EDM Afrizal Doewes, Mykola Pechenizkiy
2021	—	`conf`	ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection. EMNLP (Findings) Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection. CoRR Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency. Data Min. Knowl. Discov. Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet
2021	B	`conf`	ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks. DSAA Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
2021	A	`conf`	Self-Attention Meta-Learner for Continual Learning. AAMAS Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	J	`jnl`	Self-Attention Meta-Learner for Continual Learning. CoRR Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	A*	`conf`	Selfish Sparse RNN Training. ICML Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
2021	J	`jnl`	Selfish Sparse RNN Training. CoRR Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
2021	J	`jnl`	Semantic-Based Few-Shot Learning by Interactive Psychometric Testing. CoRR Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2021	J	`jnl`	SpaceNet: Make Free Space for Continual Learning. Neurocomputing Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	A*	`conf`	Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. NeurIPS Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2021	J	`jnl`	Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. CoRR Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2021	J	`jnl`	Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware. Neural Comput. Appl. Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy
2021	—	`conf`	Teaching Responsible Machine Learning to Engineers. Teaching ML Hilde Jacoba Petronella Weerts, Mykola Pechenizkiy
2021	J	`jnl`	The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks. CoRR Akrati Saxena, Yulong Pei, Jan Veldsink, Werner van Ipenburg, George Fletcher, Mykola Pechenizkiy
2021	J	`jnl`	The Impact of Batch Learning in Stochastic Bandits. CoRR Danil Provodin, Pratik Gajane, Mykola Pechenizkiy, Maurits Kaptein
2021	B	`conf`	The banking transactions dataset and its comparative analysis with scale-free networks. ASONAM Akrati Saxena, Yulong Pei, Jan Veldsink, Werner van Ipenburg, George Fletcher, Mykola Pechenizkiy
2021	J	`jnl`	Truly Sparse Neural Networks at Scale. CoRR Selima Curci, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	J	`jnl`	Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation. CoRR Masoud Mansoury, Himan Abdollahpouri, Bamshad Mobasher, Mykola Pechenizkiy, Robin Burke, Milad Sabouri
2021	C	`conf`	calibrated adversarial training. ACML Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2020	J	`jnl`	Bridging learning sciences, machine learning and affective computing for understanding cognition and affect in collaborative learning. Br. J. Educ. Technol. Sanna Järvelä, Dragan Gasevic, Tapio Seppänen, Mykola Pechenizkiy, Paul A. Kirschner
2020	J	`jnl`	Bridging the Performance Gap between FGSM and PGD Adversarial Training. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2020	J	`jnl`	Causal Discovery from Incomplete Data: A Deep Learning Approach. CoRR Yuhao Wang, Vlado Menkovski, Hao Wang, Xin Du, Mykola Pechenizkiy
2020	J	`jnl`	Controlling the accuracy and uncertainty trade-off in RUL prediction with a surrogate Wiener propagation model. Reliab. Eng. Syst. Saf. Yingjun Deng, Alessandro Di Bucchianico, Mykola Pechenizkiy
2020	J	`jnl`	EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features. Brain Informatics Negar Ahmadi, Yulong Pei, Evelien Carrette, Albert P. Aldenkamp, Mykola Pechenizkiy
2020	J	`jnl`	Evaluation of the Sample Clustering Process on Graphs. IEEE Trans. Knowl. Data Eng. Jianpeng Zhang, Yulong Pei, George Fletcher, Mykola Pechenizkiy
2020	J	`jnl`	Exceptional in so Many Ways - Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios. IEEE Access José María Luna, Mykola Pechenizkiy, Wouter Duivesteijn, Sebastián Ventura
2020	J	`jnl`	Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling. Data Min. Knowl. Discov. Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy
2020	A	`conf`	FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. UMAP Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	J	`jnl`	FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. CoRR Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	A*	`conf`	Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data. AAAI Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy
2020	A	`conf`	Feedback Loop and Bias Amplification in Recommender Systems. CIKM Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	J	`jnl`	Feedback Loop and Bias Amplification in Recommender Systems. CoRR Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
2020	—	`conf`	Generation of False Data Injection Attacks using Conditional Generative Adversarial Networks. ISGT-Europe Mostafa Mohammadpourfard, Fateme Ghanaatpishe, Marziyeh Mohammadi, Subhash Lakshminarayana, Mykola Pechenizkiy
2020	Misc	`conf`	Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. FLAIRS Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher
2020	J	`jnl`	Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. CoRR Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher
2020	—	`conf`	Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing. ECML/PKDD (2) Lu Yin, Vlado Menkovski, Mykola Pechenizkiy
2020	J	`jnl`	Knowledge Elicitation using Deep Metric Learning and Psychometric Testing. CoRR Lu Yin, Vlado Menkovski, Mykola Pechenizkiy
2020	J	`jnl`	Novelty Producing Synaptic Plasticity. CoRR Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy
2020	—	`conf`	Novelty producing synaptic plasticity. GECCO Companion Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George Fletcher, Mykola Pechenizkiy
2020	—	`conf`	PS3: Partition-Based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data. ECML/PKDD (5) Ricky Maulana Fajri, Samaneh Khoshrou, Robert Peharz, Mykola Pechenizkiy
2020	J	`jnl`	Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders. CoRR Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy
2020	J	`jnl`	ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks. CoRR Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
2020	J	`jnl`	SpaceNet: Make Free Space For Continual Learning. CoRR Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
2020	B	`conf`	Structural Explanation of Automated Essay Scoring. EDM Afrizal Doewes, Mykola Pechenizkiy
2020	—	`conf`	Subgraph anomaly detection in financial transaction networks. ICAIF Yulong Pei, Fang Lyu, Werner van Ipenburg, Mykola Pechenizkiy
2020	J	`jnl`	Topological Insights in Sparse Neural Networks. CoRR Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu
2020	—	`conf`	Topological Insights into Sparse Neural Networks. ECML/PKDD (3) Shiwei Liu, Tim van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu
2020	J	`jnl`	ViDi: Descriptive Visual Data Clustering as Radiologist Assistant in COVID-19 Streamline Diagnostic. CoRR Sahithya Ravi, Samaneh Khoshrou, Mykola Pechenizkiy
2020	J	`jnl`	struc2gauss: Structural role preserving network embedding via Gaussian embedding. Data Min. Knowl. Discov. Yulong Pei, Xin Du, Jianpeng Zhang, George Fletcher, Mykola Pechenizkiy
2019	J	`jnl`	A Human-Grounded Evaluation of SHAP for Alert Processing. CoRR Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy
2019	B	`conf`	Adaptive Long-Term Ensemble Learning from Multiple High-Dimensional Time-Series. DS Samaneh Khoshrou, Mykola Pechenizkiy
2019	J	`jnl`	Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data. CoRR Xin Du, Lei Sun, Wouter Duivesteijn, Alexander G. Nikolaev, Mykola Pechenizkiy
2019	J	`jnl`	BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation. CoRR Iftitahu Ni'mah, Vlado Menkovski, Mykola Pechenizkiy
2019	—	`conf`	Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. RMSE@RecSys Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy
2019	J	`jnl`	Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. CoRR Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy
2019	J	`jnl`	Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models. CoRR Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy
2019	J	`jnl`	Cluster-preserving sampling from fully-dynamic streaming graphs. Inf. Sci. Jianpeng Zhang, Kaijie Zhu, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy
2019	J	`jnl`	Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions. CoRR Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, Matt Coler, George H. L. Fletcher, Mykola Pechenizkiy
2019	B	`conf`	Infinite motif stochastic blockmodel for role discovery in networks. ASONAM Yulong Pei, Jianpeng Zhang, George H. L. Fletcher, Mykola Pechenizkiy
2019	J	`jnl`	Intrinsically Sparse Long Short-Term Memory Networks. CoRR Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy
2019	B	`conf`	Joint role and community detection in networks via ASONAM Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy
2019	J	`jnl`	Learning with Delayed Synaptic Plasticity. CoRR Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy
2019	A	`conf`	Learning with delayed synaptic plasticity. GECCO Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, George H. L. Fletcher, Mykola Pechenizkiy
2019	J	`jnl`	On improving deep learning generalization with adaptive sparse connectivity. CoRR Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy
2019	J	`jnl`	Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware. CoRR Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy
2019	—	`conf`	Supervised Human-Guided Data Exploration. PKDD/ECML Workshops (1) Emilia Oikarinen, Kai Puolamäki, Samaneh Khoshrou, Mykola Pechenizkiy
2019	J	`jnl`	The Relationship between the Consistency of Users' Ratings and Recommendation Calibration. CoRR Masoud Mansoury, Himan Abdollahpouri, Joris Rombouts, Mykola Pechenizkiy
2019	—	`conf`	VANET Meets Deep Learning: The Effect of Packet Loss on the Object Detection Performance. VTC Spring Yuhao Wang, Vlado Menkovski, Ivan Wang Hei Ho, Mykola Pechenizkiy
2018	J	`jnl`	A bounded-size clustering algorithm on fully-dynamic streaming graphs. Intell. Data Anal. Jianpeng Zhang, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy
2018	J	`jnl`	Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data. IEEE Trans. Cybern. José María Luna, Francisco Padillo, Mykola Pechenizkiy, Sebastián Ventura
2018	J	`jnl`	Assessment of visibility graph similarity as a synchronization measure for chaotic, noisy and stochastic time series. Soc. Netw. Anal. Min. Negar Ahmadi, Rene M. H. Besseling, Mykola Pechenizkiy
2018	J	`jnl`	Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally. CoRR Oren Zeev-Ben-Mordehai, Wouter Duivesteijn, Mykola Pechenizkiy
2018	A*	`conf`	DyNMF: Role Analytics in Dynamic Social Networks. IJCAI Yulong Pei, Jianpeng Zhang, George H. L. Fletcher, Mykola Pechenizkiy
2018	B	`conf`	ELBA: Exceptional Learning Behavior Analysis. EDM Xin Du, Wouter Duivesteijn, Mykola Pechenizkiy
2018	B	`conf`	Finding Predictive EEG Complexity Features for Classification of Epileptic and Psychogenic Nonepileptic Seizures Using Imperialist Competitive Algorithm. CBMS Negar Ahmadi, Evelien Carrette, Albert P. Aldenkamp, Mykola Pechenizkiy
2018	—	`conf`	ICIE 1.0: A Novel Tool for Interactive Contextual Interaction Explanations. MIDAS/PAP@PKDD/ECML Simon van der Zon, Wouter Duivesteijn, Werner van Ipenburg, Jan Veldsink, Mykola Pechenizkiy
2018	J	`jnl`	Limited Evaluation Cooperative Co-evolutionary Differential Evolution for Large-scale Neuroevolution. CoRR Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy
2018	A	`conf`	Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution. GECCO Anil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy
2018	J	`jnl`	Looking Deeper into Deep Learning Model: Attribution-based Explanations of TextCNN. CoRR Wenting Xiong, Iftitahu Ni'mah, Juan M. G. Huesca, Werner van Ipenburg, Jan Veldsink, Mykola Pechenizkiy
2018	J	`jnl`	Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming. IEEE Trans. Cybern. José María Luna, Mykola Pechenizkiy, María José del Jesus, Sebastián Ventura
2018	B	`conf`	Multi-strategy Differential Evolution. EvoApplications Anil Yaman, Giovanni Iacca, Matt Coler, George H. L. Fletcher, Mykola Pechenizkiy
2018	—	`conf`	Tink: A Temporal Graph Analytics Library for Apache Flink. WWW (Companion Volume) Wouter Ligtenberg, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy
2018	J	`jnl`	Twitter rumour detection in the health domain. Expert Syst. Appl. Rosa Sicilia, Stella Lo Giudice, Yulong Pei, Mykola Pechenizkiy, Paolo Soda
2018	J	`jnl`	struc2gauss: Structure Preserving Network Embedding via Gaussian Embedding. CoRR Yulong Pei, Xin Du, Jianpeng Zhang, George H. L. Fletcher, Mykola Pechenizkiy
2017	J	`jnl`	A white-box anomaly-based framework for database leakage detection. J. Inf. Secur. Appl. Elisa Costante, Jerry den Hartog, Milan Petkovic, Sandro Etalle, Mykola Pechenizkiy
2017	B	`conf`	BLPA: Bayesian learn-predict-adjust method for online detection of recurrent changepoints. IJCNN Alexandr V. Maslov, Mykola Pechenizkiy, Yulong Pei, Indre Zliobaite, Alexander Shklyaev, Tommi Kärkkäinen, Jaakko Hollmén
2017	—	`conf`	BoostEMM - Transparent Boosting using Exceptional Model Mining. MIDAS@PKDD/ECML Simon van der Zon, Oren Zeev-Ben-Mordehai, Tom Vrijdag, Werner van Ipenburg, Wouter Duivesteijn, Jan Veldsink, Mykola Pechenizkiy
2017	—	`conf`	Clustering-Structure Representative Sampling from Graph Streams. COMPLEX NETWORKS Jianpeng Zhang, Kaijie Zhu, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy
2017	B	`conf`	Detection of Alcoholism Based on EEG Signals and Functional Brain Network Features Extraction. CBMS Negar Ahmadi, Yulong Pei, Mykola Pechenizkiy
2017	—	`conf`	Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining. ECML/PKDD (3) Wouter Duivesteijn, Tara Farzami, Thijs Putman, Evertjan Peer, Hilde J. P. Weerts, Jasper N. Adegeest, Gerson Foks, Mykola Pechenizkiy
2017	—	`conf`	Health-related rumour detection on Twitter. BIBM Rosa Sicilia, Stella Lo Giudice, Yulong Pei, Mykola Pechenizkiy, Paolo Soda
2017	—	`conf`	How to Capitalise on Mobility, Proximity and Motion Analytics to Support Formal and Informal Education? MMLA-CrossLAK@LAK Roberto Martínez Maldonado, Augusto Dias Pereira dos Santos, Vanessa Echeverría, Kalina Yacef, Mykola Pechenizkiy
2017	A	`conf`	Modelling Embodied Mobility Teamwork Strategies in a Simulation-Based Healthcare Classroom. UMAP Roberto Martínez Maldonado, Mykola Pechenizkiy, Simon Buckingham Shum, Tamara Power, Carolyn Hayes, Carmen Axisa
2017	B	`conf`	Towards Proximity Tracking and Sensemaking for Supporting Teamwork and Learning. ICALT Roberto Martínez Maldonado, Kalina Yacef, Augusto Dias Pereira dos Santos, Simon Buckingham Shum, Vanessa Echeverría, Olga C. Santos, Mykola Pechenizkiy
2016	Misc	`conf`	A robust density-based clustering algorithm for multi-manifold structure. SAC Jianpeng Zhang, Mykola Pechenizkiy, Yulong Pei, Julia Efremova
2016	J	`jnl`	A survey on using domain and contextual knowledge for human activity recognition in video streams. Expert Syst. Appl. Leonardo Onofri, Paolo Soda, Mykola Pechenizkiy, Giulio Iannello
2016	—	`conf`	Adaptive web-based educational application for autistic students. HT (Extended Proceedings) Alejandro Montes García, Natalia Stash, Marc Fabri, Paul De Bra, George H. L. Fletcher, Mykola Pechenizkiy
2016	B	`conf`	Application of Horizontal Visibility Graph as a Robust Measure of Neurophysiological Signals Synchrony. CBMS Negar Ahmadi, Mykola Pechenizkiy
2016	Misc	`conf`	DOBRO: a prediction error correcting robot under drifts. SAC Alexandr V. Maslov, Hoang Thanh Lam, Mykola Pechenizkiy, Eric Bouillet, Tommi Kärkkäinen
2016	J	`jnl`	Editorial: A Message from the Editorial Team and an Introduction to the January-March 2016 Issue. IEEE Trans. Learn. Technol. 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
2016	—	`conf`	Explaining Soccer Match Outcomes with Goal Scoring Opportunities Predictive Analytics. MLSA@PKDD/ECML Harm Eggels, Ruud van Elk, Mykola Pechenizkiy
2016	—	`conf`	Finding Incident-Related Social Media Messages for Emergency Awareness. ECML/PKDD (3) Alexander Nieuwenhuijse, Jorn Bakker, Mykola Pechenizkiy
2016	J	`jnl`	Let's Grow Together: Tutorials on Learning Analytics Methods. J. Learn. Anal. Dragan Gasevic, Mykola Pechenizkiy
2016	J	`jnl`	Mining exceptional relationships with grammar-guided genetic programming. Knowl. Inf. Syst. José María Luna, Mykola Pechenizkiy, Sebastián Ventura
2016	A	`conf`	Modelling Recurrent Events for Improving Online Change Detection. SDM Alexandr V. Maslov, Mykola Pechenizkiy, Indre Zliobaite, Tommi Kärkkäinen
2016	Misc	`conf`	On structure preserving sampling and approximate partitioning of graphs. SAC Wouter van Heeswijk, George H. L. Fletcher, Mykola Pechenizkiy
2016	J	`jnl`	Speeding-Up Association Rule Mining With Inverted Index Compression. IEEE Trans. Cybern. José María Luna, Alberto Cano, Mykola Pechenizkiy, Sebastián Ventura
2016	B	`conf`	Structural measures of clustering quality on graph samples. ASONAM Jianpeng Zhang, Yulong Pei, George H. L. Fletcher, Mykola Pechenizkiy
2016	—	`conf`	WiBAF into a CMS: Personalization in Learning Environments Made Easy. UMAP (Extended Proceedings) Alejandro Montes García, Natalia Stash, Marc Fabri, Paul De Bra, George H. L. Fletcher, Mykola Pechenizkiy
2015	B	`conf`	Ethics and Privacy in EDM. EDM Dragan Gasevic, Taylor Martin, Zachary A. Pardos, Mykola Pechenizkiy, John C. Stamper, Osmar R. Zaïane
2015	B	`conf`	Grand Challenges for EDM and Related Research Areas. EDM Ryan S. Baker, Peter Brusilovsky, Dragan Gasevic, Neil T. Heffernan, Mykola Pechenizkiy, Alyssa Friend Wise
2015	B	`conf`	Hippocrates: A Context-Aware, Collaboration Enabling Search Tool. CBMS Georgios Aravanis, Anca I. D. Bucur, Mykola Pechenizkiy
2015	—	`ch.`	Pattern-Based Emotion Classification on Social Media. Advances in Social Media Analysis Erik Tromp, Mykola Pechenizkiy
2015	—	`conf`	Predictive analytics on evolving data streams anticipating and adapting to changes in known and unknown contexts. HPCS Mykola Pechenizkiy
2015	B	`ed.`	Proceedings of the 8th International Conference on Educational Data Mining, EDM 2015, Madrid, Spain, June 26-29, 2015 EDM 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
2015	C	`conf`	The influence of dataset size on the performance of cell outage detection approach in LTE-A networks. ICICS Sergey Chernov, Mykola Pechenizkiy, Tapani Ristaniemi
2014	—	`conf`	A DSL based on CSS for hypertext adaptation. HT Alejandro Montes García, Paul De Bra, George H. L. Fletcher, Mykola Pechenizkiy
2014	J	`jnl`	A survey on concept drift adaptation. ACM Comput. Surv. João Gama, Indre Zliobaite, Albert Bifet, Mykola Pechenizkiy, Abdelhamid Bouchachia
2014	—	`conf`	Applying Learning to Rank Techniques to Contextual Suggestions. TREC Julia Kiseleva, Alejandro Montes García, Yongming Luo, Mykola Pechenizkiy, Paul De Bra, Jaap Kamps
2014	J	`jnl`	Dealing With Concept Drifts in Process Mining. IEEE Trans. Neural Networks Learn. Syst. R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aalst, Indre Zliobaite, Mykola Pechenizkiy
2014	B	`conf`	Hunting the Unknown - White-Box Database Leakage Detection. DBSec Elisa Costante, Jerry den Hartog, Milan Petkovic, Sandro Etalle, Mykola Pechenizkiy
2014	J	`jnl`	Introduction into Sparks of the Learning Analytics Future. J. Learn. Anal. Mykola Pechenizkiy, Dragan Gasevic
2014	B	`conf`	Learning to Teach like a Bandit. EDM Mykola Pechenizkiy, Pedro A. Toledo
2014	J	`jnl`	Rule-based Emotion Detection on Social Media: Putting Tweets on Plutchik's Wheel. CoRR Erik Tromp, Mykola Pechenizkiy
2014	B	`conf`	Towards the Stress Analytics Framework: Managing, Mining, and Visualizing Multi-modal Data for Stress Awareness. CBMS Hindra Kurniawan, Mykola Pechenizkiy
2013	J	`jnl`	A comparative study of dimensionality reduction techniques to enhance trace clustering performances. Expert Syst. Appl. Minseok Song, H. Yang, Seyed Hossein Siadat, Mykola Pechenizkiy
2013	B	`conf`	ACLAC: An approach for adaptive closed-loop anesthesia control. CBMS Ayoze Marrero, Juan A. Méndez, Alexandr V. Maslov, Mykola Pechenizkiy
2013	—	`conf`	Cross-lingual polarity detection with machine translation. WISDOM Erkin Demirtas, Mykola Pechenizkiy
2013	—	`conf`	Discovering temporal hidden contexts in web sessions for user trail prediction. WWW (Companion Volume) Julia Kiseleva, Hoang Thanh Lam, Mykola Pechenizkiy, Toon Calders
2013	J	`jnl`	HyDR-MI: A hybrid algorithm to reduce dimensionality in multiple instance learning. Inf. Sci. Amelia Zafra, Mykola Pechenizkiy, Sebastián Ventura
2013	J	`jnl`	Introduction to the special issue on handling concept drift in adaptive information systems. Evol. Syst. Mykola Pechenizkiy, Indre Zliobaite
2013	—	`ed.`	New Trends in Databases and Information Systems, Workshop Proceedings of the 16th East European Conference, ADBIS 2012, Poznań, Poland, September 17-21, 2012 ADBIS Workshops Mykola Pechenizkiy, Marek Wojciechowski
2013	—	`conf`	Predicting Current User Intent with Contextual Markov Models. ICDM Workshops Julia Kiseleva, Hoang Thanh Lam, Mykola Pechenizkiy, Toon Calders
2013	J	`jnl`	Predictive Handling of Asynchronous Concept Drifts in Distributed Environments. IEEE Trans. Knowl. Data Eng. Hock Hee Ang, Vivekanand Gopalkrishnan, Indre Zliobaite, Mykola Pechenizkiy, Steven C. H. Hoi
2013	J	`jnl`	Predictive User Modeling with Actionable Attributes. CoRR Indre Zliobaite, Mykola Pechenizkiy
2013	B	`ed.`	Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, Porto, Portugal, June 20-22, 2013 CBMS Pedro Pereira Rodrigues, Mykola Pechenizkiy, João Gama, Ricardo Cruz-Correia, Jiming Liu, Agma J. M. Traina, Peter J. F. Lucas, Paolo Soda
2013	—	`conf`	RBEM: a rule based approach to polarity detection. WISDOM Erik Tromp, Mykola Pechenizkiy
2013	B	`conf`	Stress detection from speech and Galvanic Skin Response signals. CBMS Hindra Kurniawan, Alexandr V. Maslov, Mykola Pechenizkiy
2013	—	`ch.`	Techniques for Discrimination-Free Predictive Models. Discrimination and Privacy in the Information Society Faisal Kamiran, Toon Calders, Mykola Pechenizkiy
2012	J	`jnl`	Beating the baseline prediction in food sales: How intelligent an intelligent predictor is? Expert Syst. Appl. Indre Zliobaite, Jorn Bakker, Mykola Pechenizkiy
2012	B	`conf`	CurriM: Curriculum Mining. EDM Mykola Pechenizkiy, Nikola Trcka, Paul De Bra, Pedro A. Toledo
2012	B	`conf`	Mobile Sentiment Analysis. KES Lorraine Chambers, Erik Tromp, Mykola Pechenizkiy, Mohamed Medhat Gaber
2012	—	`conf`	Predicting Multi-class Customer Profiles Based on Transactions: a Case Study in Food Sales. SGAI Conf. Edward Tersoo Apeh, Indre Zliobaite, Mykola Pechenizkiy, Bogdan Gabrys
2012	B	`ed.`	Proceedings of CBMS 2012, The 25th IEEE International Symposium on Computer-Based Medical Systems, June 20-22, 2012, Rome, Italy CBMS Paolo Soda, Francesco Tortorella, Sameer K. Antani, Mykola Pechenizkiy, Mario Cannataro, Alexey Tsymbal
2012	—	`ed.`	Proceedings of the Workshop on Dynamic and Adaptive Hypertext: Generic Frameworks, Approaches and Techniques, DAH@HT 2011, Eindhoven, The Netherlands, June 6, 2011 DAH@HT Mykola Pechenizkiy, Evgeny Knutov, Michael Yudelson, Fabian Abel, Geert-Jan Houben, Eelco Herder
2012	J	`jnl`	ReliefF-MI: An extension of ReliefF to multiple instance learning. Neurocomputing Amelia Zafra, Mykola Pechenizkiy, Sebastián Ventura
2012	—	`conf`	Stess@Work: from measuring stress to its understanding, prediction and handling with personalized coaching. IHI Jorn Bakker, Leszek Holenderski, Rafal Kocielnik, Mykola Pechenizkiy, Natalia Sidorova
2012	B	`conf`	Stress Analytics in Education. EDM Rafal Kocielnik, Mykola Pechenizkiy, Natalia Sidorova
2012	J	`jnl`	Trends in computer-based medical systems. SIGHIT Rec. Paolo Soda, Sameer K. Antani, Francesco Tortorella, Mario Cannataro, Mykola Pechenizkiy, Alexey Tsymbal
2011	—	`conf`	Adaptive Hypermedia Systems Analysis Approach by Means of the GAF Framework. DAH@HT Evgeny Knutov, Paul De Bra, Mykola Pechenizkiy
2011	C	`conf`	Bridging Navigation, Search and Adaptation - Adaptive Hypermedia Models Evolution. WEBIST Evgeny Knutov, Paul De Bra, David Smits, Mykola Pechenizkiy
2011	—	`conf`	Bridging Recommendation and Adaptation: Generic Adaptation Framework - Twittomender compliance case-study. DAH@HT John Hannon, Evgeny Knutov, Paul De Bra, Mykola Pechenizkiy, Kevin McCarthy, Barry Smyth
2011	B	`conf`	Context-Aware Personal Route Recognition. Discovery Science Oleksiy Mazhelis, Indre Zliobaite, Mykola Pechenizkiy
2011	J	`jnl`	Generic Adaptation Framework: a Process-Oriented Perspective. J. Digit. Inf. Evgeny Knutov, Paul De Bra, Mykola Pechenizkiy
2011	A	`conf`	Handling Concept Drift in Process Mining. CAiSE R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aalst, Indre Zliobaite, Mykola Pechenizkiy
2011	J	`jnl`	Introduction to the special section on educational data mining. SIGKDD Explor. Toon Calders, Mykola Pechenizkiy
2011	B	`ed.`	Proceedings of the 4th International Conference on Educational Data Mining, Eindhoven, The Netherlands, July 6-8, 2011 EDM Mykola Pechenizkiy, Toon Calders, Cristina Conati, Sebastián Ventura, Cristóbal Romero, John C. Stamper
2011	—	`conf`	SentiCorr: Multilingual Sentiment Analysis of Personal Correspondence. ICDM Workshops Erik Tromp, Mykola Pechenizkiy
2011	—	`conf`	What's Your Current Stress Level? Detection of Stress Patterns from GSR Sensor Data. ICDM Workshops Jorn Bakker, Mykola Pechenizkiy, Natalia Sidorova
2010	B	`conf`	A holistic framework for understanding acceptance of Remote Patient Management (RPM) systems by non-professional users. CBMS Seppo Puuronen, Ekaterina Vasilyeva, Mykola Pechenizkiy, Aleksandra Tesanovic
2010	—	`conf`	Adaptation and search: from Dexter and AHAM to GAF. HT Evgeny Knutov, Paul De Bra, Mykola Pechenizkiy
2010	B	`conf`	Class Association Rules Mining from Students' Test Data. EDM Cristóbal Romero, Sebastián Ventura, Ekaterina Vasilyeva, Mykola Pechenizkiy
2010	A*	`conf`	Discrimination Aware Decision Tree Learning. ICDM Faisal Kamiran, Toon Calders, Mykola Pechenizkiy
2010	C	`conf`	Feature selection is the ReliefF for multiple instance learning. ISDA Amelia Zafra, Mykola Pechenizkiy, Sebastián Ventura
2010	—	`conf`	Generic Adaptation Process. WABBWUAS@UMAP Evgeny Knutov, Paul De Bra, Mykola Pechenizkiy
2010	B	`conf`	Handling concept drift in medical applications: Importance, challenges and solutions. CBMS Mykola Pechenizkiy, Indre Zliobaite
2010	B	`conf`	Heart failure hospitalization prediction in remote patient management systems. CBMS Mykola Pechenizkiy, Ekaterina Vasilyeva, Indre Zliobaite, Aleksandra Tesanovic, Goran Manev
2010	J	`jnl`	Knowledge discovery and computer-based decision support in biomedicine. Artif. Intell. Medicine Paolo Soda, Mykola Pechenizkiy, Francesco Tortorella, Alexey Tsymbal
2010	—	`conf`	Learning with Actionable Attributes: Attention -- Boundary Cases! ICDM Workshops Indre Zliobaite, Mykola Pechenizkiy
2010	—	`ed.`	Proceedings of the International Workshop on Architectures and Building Blocks of Web-Based User-Adaptive Systems, WABBWUAS@UMAP 2010, Hawaii, June 21, 2010 WABBWUAS@UMAP Fabian Abel, Eelco Herder, Geert-Jan Houben, Mykola Pechenizkiy, Michael Yudelson
2010	—	`conf`	Provenance meets adaptive hypermedia. HT Evgeny Knutov, Paul De Bra, Mykola Pechenizkiy
2010	—	`conf`	Reducing Dimensionality in Multiple Instance Learning with a Filter Method. HAIS (2) Amelia Zafra, Mykola Pechenizkiy, Sebastián Ventura
2010	B	`conf`	Towards EDM Framework for Personalization of Information Services in RPM Systems. EDM Ekaterina Vasilyeva, Mykola Pechenizkiy, Aleksandra Tesanovic, Evgeny Knutov, Sicco Verwer, Paul De Bra
2010	—	`ch.`	Towards the Generic Framework for Utility Considerations in Data Mining Research. Data Mining for Business Applications Seppo Puuronen, Mykola Pechenizkiy
2009	J	`jnl`	AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques. New Rev. Hypermedia Multim. Evgeny Knutov, Paul De Bra, Mykola Pechenizkiy
2009	—	`conf`	Building Classifiers with Independency Constraints. ICDM Workshops Toon Calders, Faisal Kamiran, Mykola Pechenizkiy
2009	—	`conf`	Dynamic and adaptive hypertext: generic frameworks, approaches and techniques. Hypertext Paul De Bra, Mykola Pechenizkiy
2009	C	`conf`	Food Wholesales Prediction: What Is Your Baseline? ISMIS Jorn Bakker, Mykola Pechenizkiy
2009	C	`conf`	From Local Patterns to Global Models: Towards Domain Driven Educational Process Mining. ISDA Nikola Trcka, Mykola Pechenizkiy
2009	J	`jnl`	Guest editorial for DKE special issue on "Biomedical Data Mining". Data Knowl. Eng. Mykola Pechenizkiy, Alexey Tsymbal
2009	—	`conf`	Handling outliers and concept drift in online mass flow prediction in CFB boilers. KDD Workshop on Knowledge Discovery from Sensor Data Jorn Bakker, Mykola Pechenizkiy, Indre Zliobaite, Andriy Ivannikov, Tommi Kärkkäinen
2009	B	`conf`	OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers. Discovery Science Indre Zliobaite, Jorn Bakker, Mykola Pechenizkiy
2009	A*	`conf`	Online Mass Flow Prediction in CFB Boilers. ICDM Andriy Ivannikov, Mykola Pechenizkiy, Jorn Bakker, Timo Leino, Mikko Jegoroff, Tommi Kärkkäinen, Sami Äyrämö
2009	J	`jnl`	Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift. SIGKDD Explor. Mykola Pechenizkiy, Jorn Bakker, Indre Zliobaite, Andriy Ivannikov, Tommi Kärkkäinen
2009	B	`conf`	Predicting Students Drop Out: A Case Study. EDM Gerben Dekker, Mykola Pechenizkiy, Jan Vleeshouwers
2009	B	`conf`	Process Mining Online Assessment Data. EDM Mykola Pechenizkiy, Nikola Trcka, Ekaterina Vasilyeva, Wil M. P. van der Aalst, Paul De Bra
2009	—	`conf`	Towards Context Aware Food Sales Prediction. ICDM Workshops Indre Zliobaite, Jorn Bakker, Mykola Pechenizkiy
2009	Misc	`conf`	Using minimum description length for process mining. SAC Toon Calders, Christian W. Günther, Mykola Pechenizkiy, Anne Rozinat
2009	B	`conf`	eHealth personalization in the next generation RPM systems. CBMS Aleksandra Tesanovic, Goran Manev, Mykola Pechenizkiy, Ekaterina Vasilyeva
2008	—	`conf`	Adaptation of Elaborated Feedback in e-Learning. AH Ekaterina Vasilyeva, Mykola Pechenizkiy, Paul De Bra
2008	B	`conf`	Defining Adaptation in a Generic Multi Layer Model: CAM: The GRAPPLE Conceptual Adaptation Model. EC-TEL Maurice Hendrix, Paul De Bra, Mykola Pechenizkiy, David Smits, Alexandra I. Cristea
2008	—	`ch.`	Does Relevance Matter to Data Mining Research?. Data Mining: Foundations and Practice Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
2008	J	`jnl`	Dynamic integration of classifiers for handling concept drift. Inf. Fusion Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham, Seppo Puuronen
2008	B	`conf`	Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance. CBMS Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal
2008	—	`conf`	Food Sales Prediction: "If Only It Knew What We Know". ICDM Workshops Patrick Meulstee, Mykola Pechenizkiy
2008	B	`conf`	Immediate Elaborated Feedback Personalization in Online Assessment. EC-TEL Ekaterina Vasilyeva, Paul De Bra, Mykola Pechenizkiy
2008	B	`conf`	Mining the Student Assessment Data: Lessons Drawn from a Small Scale Case Study. EDM Mykola Pechenizkiy, Toon Calders, Ekaterina Vasilyeva, Paul De Bra
2008	B	`conf`	Tailoring Feedback in Online Assessment: Influence of Learning Styles on the Feedback Preferences and Elaborated Feedback Effectiveness. ICALT Ekaterina Vasilyeva, Paul De Bra, Mykola Pechenizkiy, Seppo Puuronen
2008	B	`conf`	Tailoring of Feedback in Web-Based Learning: The Role of Response Certitude in the Assessment. Intelligent Tutoring Systems Ekaterina Vasilyeva, Mykola Pechenizkiy, Paul De Bra
2008	J	`jnl`	Towards more relevance-oriented data mining research. Intell. Data Anal. Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
2007	J	`jnl`	Feature Extraction for Dynamic Integration of Classifiers. Fundam. Informaticae Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen, David W. Patterson
2007	B	`conf`	Personalization of Immediate Feedback to Learning Styles. ICALT Ekaterina Vasilyeva, Mykola Pechenizkiy, Tatiana Gavrilova, Seppo Puuronen
2007	B	`conf`	Workshop on Educational Data Mining @ ICALT07 (EDM@ICALT07). ICALT Joseph E. Beck, Toon Calders, Mykola Pechenizkiy, Silvia Rita Viola
2006	B	`conf`	Class Noise and Supervised Learning in Medical Domains: The Effect of Feature Extraction. CBMS Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen, Oleksandr Pechenizkiy
2006	—	`conf`	Dynamic Integration with Random Forests. ECML Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham
2006	B	`conf`	Handling Local Concept Drift with Dynamic Integration of Classifiers: Domain of Antibiotic Resistance in Nosocomial Infections. CBMS Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham, Seppo Puuronen
2006	—	`conf`	Keynote Paper: Data Mining Researcher, Who is Your Customer? Some Issues Inspired by the Information Systems Field. DEXA Workshops Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal
2006	J	`jnl`	Local Dimensionality Reduction and Supervised Learning Within Natural Clusters for Biomedical Data Analysis. IEEE Trans. Inf. Technol. Biomed. Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
2006	B	`conf`	The Challenge of Feedback Personalization to Learning Styles in a Web-Based Learning System. ICALT Ekaterina Vasilyeva, Mykola Pechenizkiy, Seppo Puuronen
2006	Misc	`conf`	The impact of sample reduction on PCA-based feature extraction for supervised learning. SAC Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
2005	—	`conf`	Competitive Advantage from Data Mining: Some Lessons Learnt in the Information Systems Field. DEXA Workshops Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
2005	—	`conf`	Data Mining Strategy Selection via Empirical and Constructive Induction. Databases and Applications Mykola Pechenizkiy
2005	J	`jnl`	Diversity in search strategies for ensemble feature selection. Inf. Fusion Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham
2005	—	`conf`	Knowledge Discovery from Microbiology Data: Many-Sided Analysis of Antibiotic Resistance in Nosocomial Infections. Wissensmanagement (LNCS Volume) Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen, Michael A. Shifrin, Irina Alexandrova
2005	—	`conf`	Knowledge Discovery in Microbiology Data: Analysis of Antibiotic Resistance in Nosocomial Infections. Wissensmanagement Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen, Michael A. Shifrin, Irina Alexandrova
2005	—	`conf`	Knowledge Management Challenges in Knowledge Discovery Systems. DEXA Workshops Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
2005	B	`conf`	Local Dimensionality Reduction within Natural Clusters for Medical Data Analysis. CBMS Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
2005	A*	`conf`	Sequential Genetic Search for Ensemble Feature Selection. IJCAI Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham
2005	—	`conf`	The Impact of Feature Extraction on the Performance of a Classifier: kNN, Naïve Bayes and C4.5. Canadian AI Mykola Pechenizkiy
2005	B	`conf`	Towards the Framework of Adaptive User Interfaces for eHealth. CBMS Ekaterina Vasilyeva, Mykola Pechenizkiy, Seppo Puuronen
2004	B	`conf`	Diversity in Random Subspacing Ensembles. DaWaK Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham
2004	B	`conf`	PCA-based Feature Transformation for Classification: Issues in Medical Diagnostics. CBMS Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
2003	C	`conf`	Dynamic Integration of Classifiers in the Space of Principal Components. ADBIS Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen, David W. Patterson
2003	B	`conf`	Feature Extraction for Classification in Knowledge Discovery Systems. KES Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
2003	B	`conf`	Search Strategies for Ensemble Feature Selection in Medical Diagnostics. CBMS Alexey Tsymbal, Padraig Cunningham, Mykola Pechenizkiy, Seppo Puuronen
2002	Misc	`conf`	Eigenvector-Based Feature Extraction for Classification. FLAIRS Alexey Tsymbal, Seppo Puuronen, Mykola Pechenizkiy, Matthias Baumgarten, David W. Patterson