Innovative power operating center management exploiting big data techniques. - Michelangelo Ceci; Nunziato Cassavia; Roberto Corizzo; Pietro Dicosta; Donato Malerba; Gaspare Maria; Elio Masciari; Camillo Pastura (IDEAS, 2014)

Big Data Techniques For Renewable Energy Market. - Michelangelo Ceci; Nunziato Cassavia; Roberto Corizzo; Pietro Dicosta; Donato Malerba; Gaspare Maria; Elio Masciari; Camillo Pastura (SEBD, 2014)

Big Data Techniques For Supporting Accurate Predictions of Energy Production From Renewable Sources. - Michelangelo Ceci; Roberto Corizzo; Fabio Fumarola; Michele Ianni; Donato Malerba; Gaspare Maria; Elio Masciari; Marco Oliverio; Aleksandra Rashkovska (IDEAS, 2015)

VIPOC Project Research Summary (Discussion Paper). - Michelangelo Ceci; Roberto Corizzo; Fabio Fumarola; Michele Ianni; Donato Malerba; Gaspare Maria; Elio Masciari; Marco Oliverio; Aleksandra Rashkovska (SEBD, 2015)

Forecasting via Distributed Density-Based Clustering. - Roberto Corizzo; Gianvito Pio; Michelangelo Ceci; Donato Malerba (SEBD, 2017)

Predictive Modeling of PV Energy Production: How to Set Up the Learning Task for a Better Prediction? - Michelangelo Ceci; Roberto Corizzo; Fabio Fumarola; Donato Malerba; Aleksandra Rashkovska (IEEE Trans. Ind. Informatics, 2017)

An OWL Ontology for Supporting Semantic Services in Big Data Platforms. - Domenico Redavid; Roberto Corizzo; Donato Malerba (BigData Congress, 2018)

Big Data Analytics and Predictive Modeling Approaches for the Energy Sector. - Roberto Corizzo; Michelangelo Ceci; Donato Malerba (BigData Congress, 2019)

Deep Learning Versus Conventional Learning in Data Streams with Concept Drifts. - Sid Ryan; Roberto Corizzo; Iluju Kiringa; Nathalie Japkowicz (ICMLA, 2019)

Pattern and Anomaly Localization in Complex and Dynamic Data. - Sid Ryan; Roberto Corizzo; Iluju Kiringa; Nathalie Japkowicz (ICMLA, 2019)

Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data. - Roberto Corizzo; Michelangelo Ceci; Nathalie Japkowicz (Big Data Res., 2019)

Spatial autocorrelation and entropy for renewable energy forecasting. - Michelangelo Ceci; Roberto Corizzo; Donato Malerba; Aleksandra Rashkovska (Data Min. Knowl. Discov., 2019)

Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets. - Ameya Malondkar; Roberto Corizzo; Iluju Kiringa; Michelangelo Ceci; Nathalie Japkowicz (Inf. Sci., 2019)

DENCAST: distributed density-based clustering for multi-target regression. - Roberto Corizzo; Gianvito Pio; Michelangelo Ceci; Donato Malerba (J. Big Data, 2019)

One-Class Ensembles for Rare Genomic Sequences Identification. - Jonathan Kaufmann; Kathryn Asalone; Roberto Corizzo; Colin Saldanha; John R. Bracht; Nathalie Japkowicz (DS, 2020)

Short-term air pollution forecasting based on environmental factors and deep learning models. - Mirche Arsov; Eftim Zdravevski; Petre Lameski; Roberto Corizzo; Nikola Koteli; Kosta Mitreski; Vladimir Trajkovik (FedCSIS, 2020)

ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids. - Michelangelo Ceci; Roberto Corizzo; Nathalie Japkowicz; Paolo Mignone; Gianvito Pio (IEEE Access, 2020)

ReMix: Calibrated Resampling for Class Imbalance in Deep learning. - Colin Bellinger; Roberto Corizzo; Nathalie Japkowicz (CoRR, 2020)

Scalable auto-encoders for gravitational waves detection from time series data. - Roberto Corizzo; Michelangelo Ceci; Eftim Zdravevski; Nathalie Japkowicz (Expert Syst. Appl., 2020)

Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks. - Jovan Kalajdjieski; Eftim Zdravevski; Roberto Corizzo; Petre Lameski; Slobodan Kalajdziski; Ivan Miguel Pires; Nuno M. Garcia; Vladimir Trajkovik (Remote. Sens., 2020)

Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification. - Biserka Petrovska; Eftim Zdravevski; Petre Lameski; Roberto Corizzo; Ivan Stajduhar; Jonatan Lerga (Sensors, 2020)

Scalable auto-encoders for gravitational waves detection from time series data. - Roberto Corizzo; Michelangelo Ceci; Eftim Zdravevski; Nathalie Japkowicz (Zenodo, 2020)

Explainable image analysis for decision support in medical healthcare. - Roberto Corizzo; Yohan Dauphin; Colin Bellinger; Eftim Zdravevski; Nathalie Japkowicz (IEEE BigData, 2021)

WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Michael Baron; Nathalie Japkowicz (IEEE BigData, 2021)

On the combined effect of class imbalance and concept complexity in deep learning. - Kushankur Ghosh; Colin Bellinger; Roberto Corizzo; Bartosz Krawczyk; Nathalie Japkowicz (IEEE BigData, 2021)

Calibrated Resampling for Imbalanced and Long-Tails in Deep Learning. - Colin Bellinger; Roberto Corizzo; Nathalie Japkowicz (DS, 2021)

Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data. - Roberto Corizzo; Michelangelo Ceci; Gianvito Pio; Paolo Mignone; Nathalie Japkowicz (DS, 2021)

Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification. - Bartosz Krawczyk; Colin Bellinger; Roberto Corizzo; Nathalie Japkowicz (IJCNN, 2021)

Multi-aspect renewable energy forecasting. - Roberto Corizzo; Michelangelo Ceci; Hadi Fanaee-T; João Gama 001 (Inf. Sci., 2021)

Multi-Horizon Air Pollution Forecasting with Deep Neural Networks. - Mirche Arsov; Eftim Zdravevski; Petre Lameski; Roberto Corizzo; Nikola Koteli; Sasho Gramatikov; Kosta Mitreski; Vladimir Trajkovik (Sensors, 2021)

Multi-aspect renewable energy forecasting. - Roberto Corizzo; Michelangelo Ceci; Hadi Fanaee-T; João Gama 001 (Zenodo, 2021)

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. - Indranil Sur; Zachary Daniels; Abrar Rahman; Kamil Faber; Gianmarco J. Gallardo; Tyler L. Hayes; Cameron E. Taylor; Mustafa Burak Gurbuz; James Seale Smith; Sahana Pramod Joshi; Nathalie Japkowicz; Michael Baron; et al. (AIMLSystems, 2022)

Scalable Forecasting in Sensor Networks with Graph Convolutional LSTM Models. - Massimiliano Altieri; Roberto Corizzo; Michelangelo Ceci (IEEE Big Data, 2022)

Distributed Node Classification with Graph Attention Networks. - Roberto Corizzo; Terry Slenn (IEEE Big Data, 2022)

LSTM-based Pulmonary Air Leak Forecasting for Chest Tube Management. - Roberto Corizzo; Rodrigo Yepez-Lopez; Sébastien Gilbert; Nathalie Japkowicz (IEEE Big Data, 2022)

Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data. - Leah Ding; Roberto Corizzo; Colin Bellinger; Nancy Ching; Spencer Login; Rodrigo Yepez-Lopez; Jie Gong; Dong L. Wu (IEEE Big Data, 2022)

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2. - Zachary Alan Daniels; Aswin Raghavan; Jesse Hostetler; Abrar Rahman; Indranil Sur; Michael R. Piacentino; Ajay Divakaran; Roberto Corizzo; Kamil Faber; Nathalie Japkowicz; Michael Baron; James Seale Smith; et al. (CoLLAs, 2022)

Active Lifelong Anomaly Detection with Experience Replay. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (DSAA, 2022)

LIFEWATCH: Lifelong Wasserstein Change Point Detection. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Michael Baron; Nathalie Japkowicz (IJCNN, 2022)

Machine Learning for Surgical Risk Assessment Decision Systems. - Myles Russell; Dylan Russell; Roberto Corizzo; Nathalie Japkowicz (IJCNN, 2022)

4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. - Roberto Corizzo; Junfeng Ge; Colin Bellinger; Xiaoqiang Zhu; Paula Branco; Kuang-chih Lee; Nathalie Japkowicz; Ruiming Tang; Tao Zhuang; Han Zhu 001; Biye Jiang; Jiaxin Mao; et al. (KDD, 2022)

CPDGA: Change point driven growing auto-encoder for lifelong anomaly detection. - Roberto Corizzo; Michael Baron; Nathalie Japkowicz (Knowl. Based Syst., 2022)

One-GPT: A One-Class Deep Fusion Model for Machine-Generated Text Detection. - Roberto Corizzo; Sebastian Leal-Arenas (IEEE Big Data, 2023)

Multimodal One-class Learning for Malicious Online Content Detection. - Roberto Corizzo; Nora Lewis; Lucas P. Damasceno; Allison Shafer; Charles C. Cavalcante; Zois Boukouvalas (IEEE Big Data, 2023)

Distributed Continual Intrusion Detection: A Collaborative Replay Framework. - Kamil Faber; Bartlomiej Sniezynski; Roberto Corizzo (IEEE Big Data, 2023)

Distributed Concept Drift Detection for Efficient Model Adaptation with Big Data Streams. - Ian Whitehouse; Rodrigo Yepez-Lopez; Roberto Corizzo (IEEE Big Data, 2023)

Explainable Spatio-Temporal Graph Modeling. - Massimiliano Altieri; Michelangelo Ceci; Roberto Corizzo (DS, 2023)

Ada-QPacknet - Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (ECAI, 2023)

A Deep Fusion Model for Human $vs$. Machine-Generated Essay Classification. - Roberto Corizzo; Sebastian Leal-Arenas (IJCNN, 2023)

Transformed-*: A domain-incremental lifelong learning scenario generation framework. - Dominik Zurek; Roberto Corizzo; Michal Karwatowski; Marcin Pietron; Kamil Faber (IJCNN, 2023)

Performance Estimation bias in Class Imbalance with Minority Subconcepts. - Colin Bellinger; Roberto Corizzo; Nathalie Japkowicz (LIDTA, 2023)

Independent Vector Analysis with Sparse Inverse Covariance Estimation: An Application to Misinformation Detection. - Lucas P. Damasceno; Egzona Rexhepi; Allison Shafer; Ian Whitehouse; Charles C. Cavalcante; Roberto Corizzo; Zois Boukouvalas (MLSP, 2023)

Lifelong Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (CoRR, 2023)

AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2023)

Ada-QPacknet - adaptive pruning with bit width reduction as an efficient continual learning method without forgetting. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2023)

VLAD: Task-agnostic VAE-based lifelong anomaly detection. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (Neural Networks, 2023)

HURI: Hybrid user risk identification in social networks. - Roberto Corizzo; Gianvito Pio; Emanuele Pio Barracchia; Antonio Pellicani; Nathalie Japkowicz; Michelangelo Ceci (World Wide Web (WWW), 2023)

Multimodal Deep Learning for Online Meme Classification. - Stephanie Han; Sebastian Leal-Arenas; Eftim Zdravevski; Charles C. Cavalcante; Zois Boukouvalas; Roberto Corizzo (IEEE Big Data, 2024)

On the Effectiveness of Text and Image Embeddings in Multimodal Hate Speech Detection. - Nora Lewis; Charles C. Cavalcante; Zois Boukouvalas; Roberto Corizzo (IEEE Big Data, 2024)

Event-Based Multi-Modal Fusion for Online Misinformation Detection in High-Impact Events. - Javad Rajabi; Sunday Okechukwu; Ahmad Mousavi; Roberto Corizzo; Charles C. Cavalcante; Zois Boukouvalas (IEEE Big Data, 2024)

Explainable RNN Classification of Right Ventricular Dysfunction from Echocardiogram Reports. - Arun Rajaratanam; Roberto Corizzo; Zois Boukouvalas (IEEE Big Data, 2024)

Coded Term Discovery for Online Hate Speech Detection. - Dhanush Kikkisetti; Raza Ul-Mustafa; Wendy Melillo; Roberto Corizzo; Zois Boukouvalas; Jeff Gill; Nathalie Japkowicz (DSAA, 2024)

AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo; Anna Wójcik (GECCO Companion, 2024)

Towards Efficient Deep Autoencoders for Multivariate Time Series Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (ICCS (3), 2024)

Attention-Based Medical Knowledge Injection in Deep Image Classification Models. - Yaning Wu; Nathalie Japkowicz; Sébastien Gilbert; Roberto Corizzo (IJCNN, 2024)

Assessing Distance Measures for Change Point Detection in Continual Learning Scenarios. - Collin Coil; Roberto Corizzo (ISMIS, 2024)

Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. - Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz (IEEE Access, 2024)

Using LLMs to discover emerging coded antisemitic hate-speech in extremist social media. - Dhanush Kikkisetti; Raza Ul-Mustafa; Wendy Melillo; Roberto Corizzo; Zois Boukouvalas; Jeff Gill; Nathalie Japkowicz (CoRR, 2024)

AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2024)

Continual Semi-Supervised Malware Detection. - Matthew Chin; Roberto Corizzo (Mach. Learn. Knowl. Extr., 2024)

Stock market prediction with time series data and news headlines: a stacking ensemble approach. - Roberto Corizzo; Jacob Rosen (J. Intell. Inf. Syst., 2024)

Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. - Lucas P. Damasceno; Egzona Rexhepi; Allison Shafer; Ian Whitehouse; Nathalie Japkowicz; Charles C. Cavalcante; Roberto Corizzo; Zois Boukouvalas (Mach. Learn., 2024)

The class imbalance problem in deep learning. - Kushankur Ghosh; Colin Bellinger; Roberto Corizzo; Paula Branco; Bartosz Krawczyk; Nathalie Japkowicz (Mach. Learn., 2024)

Distributed and explainable GHSOM for anomaly detection in sensor networks. - Paolo Mignone; Roberto Corizzo; Michelangelo Ceci (Mach. Learn., 2024)

Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. - Lucas P. Damasceno; Egzona Rexhepi; Allison Shafer; Ian Whitehouse; Nathalie Japkowicz; Charles C. Cavalcante; Roberto Corizzo; Zois Boukouvalas (Mach. Learn., 2024)

GAP-LSTM: Graph-Based Autocorrelation Preserving Networks for Geo-Distributed Forecasting. - Massimiliano Altieri; Roberto Corizzo; Michelangelo Ceci (IEEE Trans. Neural Networks Learn. Syst., 2024)

From MNIST to ImageNet and back: benchmarking continual curriculum learning. - Kamil Faber; Dominik Zurek; Marcin Pietron; Nathalie Japkowicz; Antonio Vergari; Roberto Corizzo (Mach. Learn., 2024)

A deep fusion model for stock market prediction with news headlines and time series data. - Pinyu Chen; Zois Boukouvalas; Roberto Corizzo (Neural Comput. Appl., 2024)

Mitigating social bias in sentiment classification via ethnicity-aware algorithmic design. - Roberto Corizzo; Franziska Sofia Hafner (Soc. Netw. Anal. Min., 2024)

TinySubNets: An Efficient and Low Capacity Continual Learning Strategy. - Marcin Pietron; Kamil Faber; Dominik Zurek; Roberto Corizzo (AAAI, 2025)

pyCLAD: The universal framework for continual lifelong anomaly detection. - Kamil Faber; Bartlomiej Sniezynski; Nathalie Japkowicz; Roberto Corizzo (SoftwareX, 2025)

An end-to-end explainability framework for spatio-temporal predictive modeling. - Massimiliano Altieri; Michelangelo Ceci; Roberto Corizzo (Mach. Learn., 2025)

AD-NEv: A Scalable Multilevel Neuroevolution Framework for Multivariate Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (IEEE Trans. Neural Networks Learn. Syst., 2025)

xLSTMAD: A Powerful xLSTM-based Method for Anomaly Detection. - Kamil Faber; Marcin Pietron; Dominik Zurek; Roberto Corizzo (CoRR, 2025)

E-CaTCH: Event-Centric Cross-Modal Attention with Temporal Consistency and Class-Imbalance Handling for Misinformation Detection. - Ahmad Mousavi; Yeganeh Abdollahinejad; Roberto Corizzo; Nathalie Japkowicz; Zois Boukouvalas (CoRR, 2025)

'Slightly disappointing' vs. 'worst sh** ever': tackling cultural differences in negative sentiment expressions in AI-based sentiment analysis. - Franziska Sofia Hafner; Lena Hafner; Roberto Corizzo (J. Comput. Soc. Sci., 2025)