Mykola Pechenizkiy

Orcid: 0000-0003-4955-0743

Affiliations:
  • Eindhoven University of Technology, Netherlands


According to our database1, Mykola Pechenizkiy authored at least 308 papers between 2002 and 2024.

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Bibliography

2024
FairSNA: Algorithmic Fairness in Social Network Analysis.
ACM Comput. Surv., August, 2024

RATE-Analytics: Next Generation Predictive Analytics for Data-Driven Banking and Insurance.
Proceedings of the Commit2Data, 2024

Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML.
J. Artif. Intell. Res., 2024

FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering.
Expert Syst. Appl., 2024

Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness.
CoRR, 2024

Are Sparse Neural Networks Better Hard Sample Learners?
CoRR, 2024

Rethinking Knowledge Transfer in Learning Using Privileged Information.
CoRR, 2024

Robust Active Learning (RoAL): Countering Dynamic Adversaries in Active Learning with Elastic Weight Consolidation.
CoRR, 2024

Nerva: a Truly Sparse Implementation of Neural Networks.
CoRR, 2024

(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork.
CoRR, 2024

Dynamic Data Pruning for Automatic Speech Recognition.
CoRR, 2024

Boosting Robustness in Preference-Based Reinforcement Learning with Dynamic Sparsity.
CoRR, 2024

One-Shot Federated Learning with Bayesian Pseudocoresets.
CoRR, 2024

Learning Efficient and Fair Policies for Uncertainty-Aware Collaborative Human-Robot Order Picking.
CoRR, 2024

Exceptional Subitizing Patterns: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and Predictive Bias.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024

Adaptive Sparsity Level During Training for Efficient Time Series Forecasting with Transformers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

A Structural-Clustering Based Active Learning for Graph Neural Networks.
Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

CHAmbi: A New Benchmark on Chinese Ambiguity Challenges for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

MedINST: Meta Dataset of Biomedical Instructions.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Unveiling the Power of Sparse Neural Networks for Feature Selection.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Automatic Curriculum for Unsupervised Reinforcement Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

More than Minorities and Majorities: Understanding Multilateral Bias in Language Generation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Large Language Models Are Neurosymbolic Reasoners.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Fairness-aware fake news mitigation using counter information propagation.
Appl. Intell., November, 2023

An AI-empowered infrastructure for risk prevention during medical examination.
Expert Syst. Appl., September, 2023

Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks.
Trans. Mach. Learn. Res., 2023

Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams.
ACM Trans. Knowl. Discov. Data, 2023

GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models.
CoRR, 2023

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation.
CoRR, 2023

Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective.
CoRR, 2023

KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-Answering.
CoRR, 2023

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.
CoRR, 2023

Provably Efficient Exploration in Constrained Reinforcement Learning: Posterior Sampling Is All You Need.
CoRR, 2023

GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning.
CoRR, 2023

REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Enhancing Adversarial Training via Reweighting Optimization Trajectory.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

COOM: A Game Benchmark for Continual Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dynamic Sparsity Is Channel-Level Sparsity Learner.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LEMON: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models.
Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

Are Large Kernels Better Teachers than Transformers for ConvNets?
Proceedings of the International Conference on Machine Learning, 2023

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

FALL: A Modular Adaptive Learning Platform for Streaming Data.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Algorithmic Unfairness Through the Lens of EU Non-Discrimination Law.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Heterophily-Based Graph Neural Network for Imbalanced Classification.
Proceedings of the Complex Networks & Their Applications XII, 2023

Improving Recommender System Diversity with Variational Autoencoders.
Proceedings of the Advances in Bias and Fairness in Information Retrieval, 2023

Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems.
ACM Trans. Inf. Syst., 2022

Introduction to the Special Section on AI in Manufacturing: Current Trends and Challenges.
SIGKDD Explor., 2022

ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks.
Mach. Learn., 2022

Analyzing and repairing concept drift adaptation in data stream classification.
Mach. Learn., 2022

Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders.
Mach. Learn., 2022

A brain-inspired algorithm for training highly sparse neural networks.
Mach. Learn., 2022

Direction-aggregated Attack for Transferable Adversarial Examples.
ACM J. Emerg. Technol. Comput. Syst., 2022

HM-EIICT: Fairness-aware link prediction in complex networks using community information.
J. Comb. Optim., 2022

Mining trading patterns of pyramid schemes from financial time series data.
Future Gener. Comput. Syst., 2022

NodeSim: node similarity based network embedding for diverse link prediction.
EPJ Data Sci., 2022

Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions.
Data Min. Knowl. Discov., 2022

An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning.
CoRR, 2022

Memory-free Online Change-point Detection: A Novel Neural Network Approach.
CoRR, 2022

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity.
CoRR, 2022

Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training.
CoRR, 2022

Survey on Fair Reinforcement Learning: Theory and Practice.
CoRR, 2022

Does the End Justify the Means? On the Moral Justification of Fairness-Aware Machine Learning.
CoRR, 2022

Superposing many tickets into one: A performance booster for sparse neural network training.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS).
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Characterizing Data Scientists' Mental Models of Local Feature Importance.
Proceedings of the NordiCHI '22: Nordic Human-Computer Interaction Conference, Aarhus, Denmark, October 8, 2022

Dynamic Sparse Network for Time Series Classification: Learning What to "See".
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Where to Pay Attention in Sparse Training for Feature Selection?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Phrase-level Textual Adversarial Attack with Label Preservation.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets.
Proceedings of the Learning on Graphs Conference, 2022

Dynamic Sparse Training for Deep Reinforcement Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Semantic-Based Few-Shot Classification by Psychometric Learning.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity.
Proceedings of the Tenth International Conference on Learning Representations, 2022

The Impact of Batch Learning in Stochastic Linear Bandits.
Proceedings of the IEEE International Conference on Data Mining, 2022

FATED 2022: Fairness, Accountability, and Transparency in Educational Data.
Proceedings of the 15th International Conference on Educational Data Mining, 2022

Individual Fairness Evaluation for Automated Essay Scoring System.
Proceedings of the 15th International Conference on Educational Data Mining, 2022

A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams.
Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

LevDoom: A Benchmark for Generalization on Level Difficulty in Reinforcement Learning.
Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

2021
Introduction to The Special Section on Bias and Fairness in AI.
SIGKDD Explor., 2021

Efficient and effective training of sparse recurrent neural networks.
Neural Comput. Appl., 2021

Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware.
Neural Comput. Appl., 2021

SpaceNet: Make Free Space for Continual Learning.
Neurocomputing, 2021

Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions.
Evol. Comput., 2021

Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency.
Data Min. Knowl. Discov., 2021

Adversarial balancing-based representation learning for causal effect inference with observational data.
Data Min. Knowl. Discov., 2021

Semantic-Based Few-Shot Learning by Interactive Psychometric Testing.
CoRR, 2021

The Impact of Batch Learning in Stochastic Bandits.
CoRR, 2021

Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning.
CoRR, 2021

Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles.
CoRR, 2021

Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation.
CoRR, 2021

FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity.
CoRR, 2021

How Fair is Fairness-aware Representative Ranking and Methods for Fair Ranking.
CoRR, 2021

Truly Sparse Neural Networks at Scale.
CoRR, 2021

Learning Invariant Representation for Continual Learning.
CoRR, 2021

How Fair is Fairness-aware Representative Ranking?
Proceedings of the Companion of The Web Conference 2021, 2021

Teaching Responsible Machine Learning to Engineers.
Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, 2021

On Generalization of Graph Autoencoders with Adversarial Training.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training.
Proceedings of the 38th International Conference on Machine Learning, 2021

Selfish Sparse RNN Training.
Proceedings of the 38th International Conference on Machine Learning, 2021

Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

On the Limitations of Human-Computer Agreement in Automated Essay Scoring.
Proceedings of the 14th International Conference on Educational Data Mining, 2021

Self-Attention Meta-Learner for Continual Learning.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

The banking transactions dataset and its comparative analysis with scale-free networks.
Proceedings of the ASONAM '21: International Conference on Advances in Social Networks Analysis and Mining, Virtual Event, The Netherlands, November 8, 2021

Hierarchical Semantic Segmentation using Psychometric Learning.
Proceedings of the Asian Conference on Machine Learning, 2021

calibrated adversarial training.
Proceedings of the Asian Conference on Machine Learning, 2021

2020
Evaluation of the Sample Clustering Process on Graphs.
IEEE Trans. Knowl. Data Eng., 2020

Controlling the accuracy and uncertainty trade-off in RUL prediction with a surrogate Wiener propagation model.
Reliab. Eng. Syst. Saf., 2020

struc2gauss: Structural role preserving network embedding via Gaussian embedding.
Data Min. Knowl. Discov., 2020

Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling.
Data Min. Knowl. Discov., 2020

ViDi: Descriptive Visual Data Clustering as Radiologist Assistant in COVID-19 Streamline Diagnostic.
CoRR, 2020

Bridging the Performance Gap between FGSM and PGD Adversarial Training.
CoRR, 2020

Topological Insights in Sparse Neural Networks.
CoRR, 2020

Causal Discovery from Incomplete Data: A Deep Learning Approach.
CoRR, 2020

EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features.
Brain Informatics, 2020

Bridging learning sciences, machine learning and affective computing for understanding cognition and affect in collaborative learning.
Br. J. Educ. Technol., 2020

Exceptional in so Many Ways - Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios.
IEEE Access, 2020

FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems.
Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, 2020

Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Topological Insights into Sparse Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

PS3: Partition-Based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Generation of False Data Injection Attacks using Conditional Generative Adversarial Networks.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2020

Subgraph anomaly detection in financial transaction networks.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

Novelty producing synaptic plasticity.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems.
Proceedings of the Thirty-Third International Florida Artificial Intelligence Research Society Conference, 2020

Structural Explanation of Automated Essay Scoring.
Proceedings of the 13th International Conference on Educational Data Mining, 2020

Feedback Loop and Bias Amplification in Recommender Systems.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Cluster-preserving sampling from fully-dynamic streaming graphs.
Inf. Sci., 2019

The Relationship between the Consistency of Users' Ratings and Recommendation Calibration.
CoRR, 2019

BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation.
CoRR, 2019

Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models.
CoRR, 2019

A Human-Grounded Evaluation of SHAP for Alert Processing.
CoRR, 2019

On improving deep learning generalization with adaptive sparse connectivity.
CoRR, 2019

Intrinsically Sparse Long Short-Term Memory Networks.
CoRR, 2019

VANET Meets Deep Learning: The Effect of Packet Loss on the Object Detection Performance.
Proceedings of the 89th IEEE Vehicular Technology Conference, 2019

Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison.
Proceedings of the Workshop on Recommendation in Multi-stakeholder Environments co-located with the 13th ACM Conference on Recommender Systems (RecSys 2019), 2019

Supervised Human-Guided Data Exploration.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Learning with delayed synaptic plasticity.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Adaptive Long-Term Ensemble Learning from Multiple High-Dimensional Time-Series.
Proceedings of the Discovery Science - 22nd International Conference, 2019

Infinite motif stochastic blockmodel for role discovery in networks.
Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

Joint role and community detection in networks via <i>L</i><sub>2, 1</sub> norm regularized nonnegative matrix tri-factorization.
Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018
Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data.
IEEE Trans. Cybern., 2018

Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.
IEEE Trans. Cybern., 2018

Assessment of visibility graph similarity as a synchronization measure for chaotic, noisy and stochastic time series.
Soc. Netw. Anal. Min., 2018

A bounded-size clustering algorithm on fully-dynamic streaming graphs.
Intell. Data Anal., 2018

Twitter rumour detection in the health domain.
Expert Syst. Appl., 2018

Looking Deeper into Deep Learning Model: Attribution-based Explanations of TextCNN.
CoRR, 2018

Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally.
CoRR, 2018

struc2gauss: Structure Preserving Network Embedding via Gaussian Embedding.
CoRR, 2018

Tink: A Temporal Graph Analytics Library for Apache Flink.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

ICIE 1.0: A Novel Tool for Interactive Contextual Interaction Explanations.
Proceedings of the ECML PKDD 2018 Workshops, 2018

DyNMF: Role Analytics in Dynamic Social Networks.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Multi-strategy Differential Evolution.
Proceedings of the Applications of Evolutionary Computation, 2018

ELBA: Exceptional Learning Behavior Analysis.
Proceedings of the 11th International Conference on Educational Data Mining, 2018

Finding Predictive EEG Complexity Features for Classification of Epileptic and Psychogenic Nonepileptic Seizures Using Imperialist Competitive Algorithm.
Proceedings of the 31st IEEE International Symposium on Computer-Based Medical Systems, 2018

2017
A white-box anomaly-based framework for database leakage detection.
J. Inf. Secur. Appl., 2017

Modelling Embodied Mobility Teamwork Strategies in a Simulation-Based Healthcare Classroom.
Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

BoostEMM - Transparent Boosting using Exceptional Model Mining.
Proceedings of the Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), 2017

Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

How to Capitalise on Mobility, Proximity and Motion Analytics to Support Formal and Informal Education?
Proceedings of the Joint Proceedings of the Sixth Multimodal Learning Analytics (MMLA) Workshop and the Second Cross-LAK Workshop co-located with 7th International Learning Analytics and Knowledge Conference (LAK 2017), 2017

BLPA: Bayesian learn-predict-adjust method for online detection of recurrent changepoints.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Towards Proximity Tracking and Sensemaking for Supporting Teamwork and Learning.
Proceedings of the 17th IEEE International Conference on Advanced Learning Technologies, 2017

Clustering-Structure Representative Sampling from Graph Streams.
Proceedings of the Complex Networks & Their Applications VI, 2017

Detection of Alcoholism Based on EEG Signals and Functional Brain Network Features Extraction.
Proceedings of the 30th IEEE International Symposium on Computer-Based Medical Systems, 2017

Health-related rumour detection on Twitter.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016
Let's Grow Together: Tutorials on Learning Analytics Methods.
J. Learn. Anal., December, 2016

Editorial: A Message from the Editorial Team and an Introduction to the January-March 2016 Issue.
IEEE Trans. Learn. Technol., 2016

Speeding-Up Association Rule Mining With Inverted Index Compression.
IEEE Trans. Cybern., 2016

Mining exceptional relationships with grammar-guided genetic programming.
Knowl. Inf. Syst., 2016

A survey on using domain and contextual knowledge for human activity recognition in video streams.
Expert Syst. Appl., 2016

WiBAF into a CMS: Personalization in Learning Environments Made Easy.
Proceedings of the Late-breaking Results, 2016

Modelling Recurrent Events for Improving Online Change Detection.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

A robust density-based clustering algorithm for multi-manifold structure.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

DOBRO: a prediction error correcting robot under drifts.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

On structure preserving sampling and approximate partitioning of graphs.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Finding Incident-Related Social Media Messages for Emergency Awareness.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Explaining Soccer Match Outcomes with Goal Scoring Opportunities Predictive Analytics.
Proceedings of the Workshop on Machine Learning and Data Mining for Sports Analytics 2016 co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016

Adaptive web-based educational application for autistic students.
Proceedings of the Late-breaking Results, 2016

Application of Horizontal Visibility Graph as a Robust Measure of Neurophysiological Signals Synchrony.
Proceedings of the 29th IEEE International Symposium on Computer-Based Medical Systems, 2016

Structural measures of clustering quality on graph samples.
Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2016

2015
Pattern-Based Emotion Classification on Social Media.
Proceedings of the Advances in Social Media Analysis, 2015

Predictive analytics on evolving data streams anticipating and adapting to changes in known and unknown contexts.
Proceedings of the 2015 International Conference on High Performance Computing & Simulation, 2015

Ethics and Privacy in EDM.
Proceedings of the 8th International Conference on Educational Data Mining, 2015

Grand Challenges for EDM and Related Research Areas.
Proceedings of the 8th International Conference on Educational Data Mining, 2015

Hippocrates: A Context-Aware, Collaboration Enabling Search Tool.
Proceedings of the 28th IEEE International Symposium on Computer-Based Medical Systems, 2015

The influence of dataset size on the performance of cell outage detection approach in LTE-A networks.
Proceedings of the 10th International Conference on Information, 2015

2014
Introduction into Sparks of the Learning Analytics Future.
J. Learn. Anal., November, 2014

Dealing With Concept Drifts in Process Mining.
IEEE Trans. Neural Networks Learn. Syst., 2014

A survey on concept drift adaptation.
ACM Comput. Surv., 2014

Rule-based Emotion Detection on Social Media: Putting Tweets on Plutchik's Wheel.
CoRR, 2014

Applying Learning to Rank Techniques to Contextual Suggestions.
Proceedings of The Twenty-Third Text REtrieval Conference, 2014

A DSL based on CSS for hypertext adaptation.
Proceedings of the 25th ACM Conference on Hypertext and Social Media, 2014

Learning to Teach like a Bandit.
Proceedings of the 7th International Conference on Educational Data Mining, 2014

Hunting the Unknown - White-Box Database Leakage Detection.
Proceedings of the Data and Applications Security and Privacy XXVIII, 2014

Towards the Stress Analytics Framework: Managing, Mining, and Visualizing Multi-modal Data for Stress Awareness.
Proceedings of the 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, 2014

2013
Techniques for Discrimination-Free Predictive Models.
Proceedings of the Discrimination and Privacy in the Information Society, 2013

Predictive Handling of Asynchronous Concept Drifts in Distributed Environments.
IEEE Trans. Knowl. Data Eng., 2013

HyDR-MI: A hybrid algorithm to reduce dimensionality in multiple instance learning.
Inf. Sci., 2013

Introduction to the special issue on handling concept drift in adaptive information systems.
Evol. Syst., 2013

A comparative study of dimensionality reduction techniques to enhance trace clustering performances.
Expert Syst. Appl., 2013

Predictive User Modeling with Actionable Attributes.
CoRR, 2013

Discovering temporal hidden contexts in web sessions for user trail prediction.
Proceedings of the 22nd International World Wide Web Conference, 2013

RBEM: a rule based approach to polarity detection.
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining, 2013

Cross-lingual polarity detection with machine translation.
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining, 2013

Predicting Current User Intent with Contextual Markov Models.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

ACLAC: An approach for adaptive closed-loop anesthesia control.
Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, 2013

Stress detection from speech and Galvanic Skin Response signals.
Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, 2013

2012
Trends in computer-based medical systems.
SIGHIT Rec., 2012

ReliefF-MI: An extension of ReliefF to multiple instance learning.
Neurocomputing, 2012

Beating the baseline prediction in food sales: How intelligent an intelligent predictor is?
Expert Syst. Appl., 2012

Predicting Multi-class Customer Profiles Based on Transactions: a Case Study in Food Sales.
Proceedings of the Research and Development in Intelligent Systems XXIX, 2012

Mobile Sentiment Analysis.
Proceedings of the Advances in Knowledge-Based and Intelligent Information and Engineering Systems, 2012

Stess@Work: from measuring stress to its understanding, prediction and handling with personalized coaching.
Proceedings of the ACM International Health Informatics Symposium, 2012

CurriM: Curriculum Mining.
Proceedings of the 5th International Conference on Educational Data Mining, 2012

Stress Analytics in Education.
Proceedings of the 5th International Conference on Educational Data Mining, 2012

2011
Introduction to the special section on educational data mining.
SIGKDD Explor., 2011

Generic Adaptation Framework: a Process-Oriented Perspective.
J. Digit. Inf., 2011

Bridging Navigation, Search and Adaptation - Adaptive Hypermedia Models Evolution.
Proceedings of the WEBIST 2011, 2011

SentiCorr: Multilingual Sentiment Analysis of Personal Correspondence.
Proceedings of the Data Mining Workshops (ICDMW), 2011

What's Your Current Stress Level? Detection of Stress Patterns from GSR Sensor Data.
Proceedings of the Data Mining Workshops (ICDMW), 2011

Adaptive Hypermedia Systems Analysis Approach by Means of the GAF Framework.
Proceedings of the Workshop on Dynamic and Adaptive Hypertext: Generic Frameworks, 2011

Bridging Recommendation and Adaptation: Generic Adaptation Framework - Twittomender compliance case-study.
Proceedings of the Workshop on Dynamic and Adaptive Hypertext: Generic Frameworks, 2011

Context-Aware Personal Route Recognition.
Proceedings of the Discovery Science - 14th International Conference, 2011

Handling Concept Drift in Process Mining.
Proceedings of the Advanced Information Systems Engineering, 2011

2010
Towards the Generic Framework for Utility Considerations in Data Mining Research.
Proceedings of the Data Mining for Business Applications, 2010

Knowledge discovery and computer-based decision support in biomedicine.
Artif. Intell. Medicine, 2010

Generic Adaptation Process.
Proceedings of the International Workshop on Architectures and Building Blocks of Web-Based User-Adaptive Systems, 2010

Feature selection is the ReliefF for multiple instance learning.
Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, 2010

Learning with Actionable Attributes: Attention -- Boundary Cases!
Proceedings of the ICDMW 2010, 2010

Discrimination Aware Decision Tree Learning.
Proceedings of the ICDM 2010, 2010

Adaptation and search: from Dexter and AHAM to GAF.
Proceedings of the HT'10, 2010

Provenance meets adaptive hypermedia.
Proceedings of the HT'10, 2010

Reducing Dimensionality in Multiple Instance Learning with a Filter Method.
Proceedings of the Hybrid Artificial Intelligence Systems, 5th International Conference, 2010

Towards EDM Framework for Personalization of Information Services in RPM Systems.
Proceedings of the Educational Data Mining 2010, 2010

Class Association Rules Mining from Students' Test Data.
Proceedings of the Educational Data Mining 2010, 2010

A holistic framework for understanding acceptance of Remote Patient Management (RPM) systems by non-professional users.
Proceedings of the IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), 2010

Handling concept drift in medical applications: Importance, challenges and solutions.
Proceedings of the IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), 2010

Heart failure hospitalization prediction in remote patient management systems.
Proceedings of the IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), 2010

2009
Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift.
SIGKDD Explor., 2009

AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques.
New Rev. Hypermedia Multim., 2009

Guest editorial for DKE special issue on "Biomedical Data Mining".
Data Knowl. Eng., 2009

Using minimum description length for process mining.
Proceedings of the 2009 ACM Symposium on Applied Computing (SAC), 2009

Handling outliers and concept drift in online mass flow prediction in CFB boilers.
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, 2009

Food Wholesales Prediction: What Is Your Baseline?
Proceedings of the Foundations of Intelligent Systems, 18th International Symposium, 2009

From Local Patterns to Global Models: Towards Domain Driven Educational Process Mining.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

Online Mass Flow Prediction in CFB Boilers.
Proceedings of the Advances in Data Mining. Applications and Theoretical Aspects, 2009

Towards Context Aware Food Sales Prediction.
Proceedings of the ICDM Workshops 2009, 2009

Building Classifiers with Independency Constraints.
Proceedings of the ICDM Workshops 2009, 2009

Dynamic and adaptive hypertext: generic frameworks, approaches and techniques.
Proceedings of the HYPERTEXT 2009, Proceedings of the 20th ACM Conference on Hypertext and Hypermedia, Torino, Italy, June 29, 2009

Process Mining Online Assessment Data.
Proceedings of the Educational Data Mining, 2009

Predicting Students Drop Out: A Case Study.
Proceedings of the Educational Data Mining, 2009

OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers.
Proceedings of the Discovery Science, 12th International Conference, 2009

eHealth personalization in the next generation RPM systems.
Proceedings of the Twenty-Second IEEE International Symposium on Computer-Based Medical Systems, 2009

2008
Does Relevance Matter to Data Mining Research?.
Proceedings of the Data Mining: Foundations and Practice, 2008

Dynamic integration of classifiers for handling concept drift.
Inf. Fusion, 2008

Towards more relevance-oriented data mining research.
Intell. Data Anal., 2008

Tailoring of Feedback in Web-Based Learning: The Role of Response Certitude in the Assessment.
Proceedings of the Intelligent Tutoring Systems, 9th International Conference, 2008

Food Sales Prediction: "If Only It Knew What We Know".
Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Tailoring Feedback in Online Assessment: Influence of Learning Styles on the Feedback Preferences and Elaborated Feedback Effectiveness.
Proceedings of the 8th IEEE International Conference on Advanced Learning Technologies, 2008

Mining the Student Assessment Data: Lessons Drawn from a Small Scale Case Study.
Proceedings of the Educational Data Mining 2008, 2008

Immediate Elaborated Feedback Personalization in Online Assessment.
Proceedings of the Times of Convergence. Technologies Across Learning Contexts, 2008

Defining Adaptation in a Generic Multi Layer Model: CAM: The GRAPPLE Conceptual Adaptation Model.
Proceedings of the Times of Convergence. Technologies Across Learning Contexts, 2008

Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance.
Proceedings of the Twenty-First IEEE International Symposium on Computer-Based Medical Systems, 2008

Adaptation of Elaborated Feedback in e-Learning.
Proceedings of the Adaptive Hypermedia and Adaptive Web-Based Systems, 2008

2007
Feature Extraction for Dynamic Integration of Classifiers.
Fundam. Informaticae, 2007

Personalization of Immediate Feedback to Learning Styles.
Proceedings of the 7th IEEE International Conference on Advanced Learning Technologies, 2007

Workshop on Educational Data Mining @ ICALT07 (EDM@ICALT07).
Proceedings of the 7th IEEE International Conference on Advanced Learning Technologies, 2007

2006
Local Dimensionality Reduction and Supervised Learning Within Natural Clusters for Biomedical Data Analysis.
IEEE Trans. Inf. Technol. Biomed., 2006

The impact of sample reduction on PCA-based feature extraction for supervised learning.
Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

The Challenge of Feedback Personalization to Learning Styles in a Web-Based Learning System.
Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies, 2006

Dynamic Integration with Random Forests.
Proceedings of the Machine Learning: ECML 2006, 2006

Keynote Paper: Data Mining Researcher, Who is Your Customer? Some Issues Inspired by the Information Systems Field.
Proceedings of the 17th International Workshop on Database and Expert Systems Applications (DEXA 2006), 2006

Handling Local Concept Drift with Dynamic Integration of Classifiers: Domain of Antibiotic Resistance in Nosocomial Infections.
Proceedings of the 19th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2006), 2006

Class Noise and Supervised Learning in Medical Domains: The Effect of Feature Extraction.
Proceedings of the 19th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2006), 2006

2005
Diversity in search strategies for ensemble feature selection.
Inf. Fusion, 2005

Knowledge Discovery in Microbiology Data: Analysis of Antibiotic Resistance in Nosocomial Infections.
Proceedings of the WM 2005: Professional Knowledge Management - Experiences and Visions, Contributions to the 3rd Conference Professional Knowledge Management, 2005

Knowledge Discovery from Microbiology Data: Many-Sided Analysis of Antibiotic Resistance in Nosocomial Infections.
Proceedings of the Professional Knowledge Management, Third Biennial Conference, 2005

Sequential Genetic Search for Ensemble Feature Selection.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Knowledge Management Challenges in Knowledge Discovery Systems.
Proceedings of the 16th International Workshop on Database and Expert Systems Applications (DEXA 2005), 2005

Competitive Advantage from Data Mining: Some Lessons Learnt in the Information Systems Field.
Proceedings of the 16th International Workshop on Database and Expert Systems Applications (DEXA 2005), 2005

Data Mining Strategy Selection via Empirical and Constructive Induction.
Proceedings of the IASTED International Conference on Databases and Applications, 2005

Towards the Framework of Adaptive User Interfaces for eHealth.
Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems (CBMS 2005), 2005

Local Dimensionality Reduction within Natural Clusters for Medical Data Analysis.
Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems (CBMS 2005), 2005

The Impact of Feature Extraction on the Performance of a Classifier: kNN, Naïve Bayes and C4.5.
Proceedings of the Advances in Artificial Intelligence, 2005

2004
Diversity in Random Subspacing Ensembles.
Proceedings of the Data Warehousing and Knowledge Discovery, 6th International Conference, 2004

PCA-based Feature Transformation for Classification: Issues in Medical Diagnostics.
Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems (CBMS 2004), 2004

2003
Feature Extraction for Classification in Knowledge Discovery Systems.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003

Search Strategies for Ensemble Feature Selection in Medical Diagnostics.
Proceedings of the 16th IEEE Symposium on Computer-Based Medical Systems (CBMS 2003), 2003

Dynamic Integration of Classifiers in the Space of Principal Components.
Proceedings of the Advances in Databases and Information Systems, 2003

2002
Eigenvector-Based Feature Extraction for Classification.
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference, 2002


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