Roberto Corizzo

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 69

Top Topics

Spatial Autocorrelation

Anomaly Detection

Top Venues

Publications

Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. Mach. Learn. 113 (9) (2024)
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. IEEE Access 12 (2024)
Paolo Mignone, Roberto Corizzo, Michelangelo Ceci
Distributed and explainable GHSOM for anomaly detection in sensor networks. Mach. Learn. 113 (7) (2024)
Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo
Towards Efficient Deep Autoencoders for Multivariate Time Series Anomaly Detection. ICCS (3) (2024)
Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo
AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework. CoRR (2024)
Collin Coil, Roberto Corizzo
Assessing Distance Measures for Change Point Detection in Continual Learning Scenarios. ISMIS (2024)
Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo, Anna Wójcik
AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework. GECCO Companion (2024)
Roberto Corizzo, Jacob Rosen
Stock market prediction with time series data and news headlines: a stacking ensemble approach. J. Intell. Inf. Syst. 62 (1) (2024)
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Paula Branco, Bartosz Krawczyk, Nathalie Japkowicz
The class imbalance problem in deep learning. Mach. Learn. 113 (7) (2024)
Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. Mach. Learn. 113 (4) (2024)
Dhanush Kikkisetti, Raza Ul-Mustafa, Wendy Melillo, Roberto Corizzo, Zois Boukouvalas, Jeff Gill, Nathalie Japkowicz
Using LLMs to discover emerging coded antisemitic hate-speech in extremist social media. CoRR (2024)
Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo
Towards efficient deep autoencoders for multivariate time series anomaly detection. CoRR (2024)
Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
Performance Estimation bias in Class Imbalance with Minority Subconcepts. LIDTA (2023)
Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo
From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning. CoRR (2023)
Roberto Corizzo, Sebastian Leal-Arenas
One-GPT: A One-Class Deep Fusion Model for Machine-Generated Text Detection. BigData (2023)
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz
Lifelong Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. CoRR (2023)
Roberto Corizzo, Gianvito Pio, Emanuele Pio Barracchia, Antonio Pellicani, Nathalie Japkowicz, Michelangelo Ceci
HURI: Hybrid user risk identification in social networks. World Wide Web (WWW) 26 (5) (2023)
Massimiliano Altieri, Michelangelo Ceci, Roberto Corizzo
Explainable Spatio-Temporal Graph Modeling. DS (2023)
Roberto Corizzo, Nora Lewis, Lucas P. Damasceno, Allison Shafer, Charles C. Cavalcante, Zois Boukouvalas
Multimodal One-class Learning for Malicious Online Content Detection. BigData (2023)
Roberto Corizzo, Sebastian Leal-Arenas
A Deep Fusion Model for Human $vs$. Machine-Generated Essay Classification. IJCNN (2023)
Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo
Ada-QPacknet - adaptive pruning with bit width reduction as an efficient continual learning method without forgetting. CoRR (2023)
Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas
Independent Vector Analysis with Sparse Inverse Covariance Estimation: An Application to Misinformation Detection. MLSP (2023)
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz
VLAD: Task-agnostic VAE-based lifelong anomaly detection. Neural Networks 165 (2023)
Dominik Zurek, Roberto Corizzo, Michal Karwatowski, Marcin Pietron, Kamil Faber
Transformed-*: A domain-incremental lifelong learning scenario generation framework. IJCNN (2023)
Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo
AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection. CoRR (2023)
Kamil Faber, Bartlomiej Sniezynski, Roberto Corizzo
Distributed Continual Intrusion Detection: A Collaborative Replay Framework. BigData (2023)
Ian Whitehouse, Rodrigo Yepez-Lopez, Roberto Corizzo
Distributed Concept Drift Detection for Efficient Model Adaptation with Big Data Streams. BigData (2023)
Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo
Ada-QPacknet - Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning. ECAI (2023)
Massimiliano Altieri, Roberto Corizzo, Michelangelo Ceci
Scalable Forecasting in Sensor Networks with Graph Convolutional LSTM Models. Big Data (2022)
Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. KDD (2022)
Roberto Corizzo, Rodrigo Yepez-Lopez, Sébastien Gilbert, Nathalie Japkowicz
LSTM-based Pulmonary Air Leak Forecasting for Chest Tube Management. Big Data (2022)
Leah Ding, Roberto Corizzo, Colin Bellinger, Nancy Ching, Spencer Login, Rodrigo Yepez-Lopez, Jie Gong, Dong L. Wu
Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data. Big Data (2022)
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, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael Piacentino, Jesse Hostetler, Aswin Raghavan
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. AIMLSystems (2022)
Zachary Alan Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael Piacentino, Ajay Divakaran, Roberto Corizzo, Kamil Faber, Nathalie Japkowicz, Michael Baron, James Seale Smith, Sahana Pramod Joshi, Zsolt Kira, Cameron Ethan Taylor, Mustafa Burak Gurbuz, Constantine Dovrolis, Tyler L. Hayes, Christopher Kanan, Jhair Gallardo
Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2. CoLLAs (2022)
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz
Active Lifelong Anomaly Detection with Experience Replay. DSAA (2022)
Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Seale Smith, Sahana Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael R. Piacentino, Jesse Hostetler, Aswin Raghavan
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. CoRR (2022)
Roberto Corizzo, Terry Slenn
Distributed Node Classification with Graph Attention Networks. Big Data (2022)
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. CoRR (2022)
Myles Russell, Dylan Russell, Roberto Corizzo, Nathalie Japkowicz
Machine Learning for Surgical Risk Assessment Decision Systems. IJCNN (2022)
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz
LIFEWATCH: Lifelong Wasserstein Change Point Detection. IJCNN (2022)
Roberto Corizzo, Michael Baron, Nathalie Japkowicz
CPDGA: Change point driven growing auto-encoder for lifelong anomaly detection. Knowl. Based Syst. 247 (2022)
Bartosz Krawczyk, Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification. IJCNN (2021)
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. IEEE BigData (2021)
Roberto Corizzo, Yohan Dauphin, Colin Bellinger, Eftim Zdravevski, Nathalie Japkowicz
Explainable image analysis for decision support in medical healthcare. IEEE BigData (2021)
Mirche Arsov, Eftim Zdravevski, Petre Lameski, Roberto Corizzo, Nikola Koteli, Sasho Gramatikov, Kosta Mitreski, Vladimir Trajkovik
Multi-Horizon Air Pollution Forecasting with Deep Neural Networks. Sensors 21 (4) (2021)
Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
Calibrated Resampling for Imbalanced and Long-Tails in Deep Learning. DS (2021)
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz
On the combined effect of class imbalance and concept complexity in deep learning. IEEE BigData (2021)
Roberto Corizzo, Michelangelo Ceci, Gianvito Pio, Paolo Mignone, Nathalie Japkowicz
Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data. DS (2021)
Roberto Corizzo, Michelangelo Ceci, Hadi Fanaee-T, João Gama
Multi-aspect renewable energy forecasting. Inf. Sci. 546 (2021)
Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz
On the combined effect of class imbalance and concept complexity in deep learning. CoRR (2021)
Michelangelo Ceci, Roberto Corizzo, Nathalie Japkowicz, Paolo Mignone, Gianvito Pio
ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids. IEEE Access 8 (2020)
Mirche Arsov, Eftim Zdravevski, Petre Lameski, Roberto Corizzo, Nikola Koteli, Kosta Mitreski, Vladimir Trajkovik
Short-term air pollution forecasting based on environmental factors and deep learning models. FedCSIS (2020)
Jonathan Kaufmann, Kathryn Asalone, Roberto Corizzo, Colin Saldanha, John Bracht, Nathalie Japkowicz
One-Class Ensembles for Rare Genomic Sequences Identification. DS (2020)
Jovan Kalajdjieski, Eftim Zdravevski, Roberto Corizzo, Petre Lameski, Slobodan Kalajdziski, Ivan Miguel Pires, Nuno M. Garcia, Vladimir Trajkovik
Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks. Remote. Sens. 12 (24) (2020)
Biserka Petrovska, Eftim Zdravevski, Petre Lameski, Roberto Corizzo, Ivan Stajduhar, Jonatan Lerga
Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification. Sensors 20 (14) (2020)
Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
ReMix: Calibrated Resampling for Class Imbalance in Deep learning. CoRR (2020)
Roberto Corizzo, Michelangelo Ceci, Eftim Zdravevski, Nathalie Japkowicz
Scalable auto-encoders for gravitational waves detection from time series data. Expert Syst. Appl. 151 (2020)
Michelangelo Ceci, Roberto Corizzo, Donato Malerba, Aleksandra Rashkovska
Spatial autocorrelation and entropy for renewable energy forecasting. Data Min. Knowl. Discov. 33 (3) (2019)
Ameya Malondkar, Roberto Corizzo, Iluju Kiringa, Michelangelo Ceci, Nathalie Japkowicz
Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets. Inf. Sci. 496 (2019)
Roberto Corizzo, Gianvito Pio, Michelangelo Ceci, Donato Malerba
DENCAST: distributed density-based clustering for multi-target regression. J. Big Data 6 (2019)
Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz
Pattern and Anomaly Localization in Complex and Dynamic Data. ICMLA (2019)
Roberto Corizzo, Michelangelo Ceci, Donato Malerba
Big Data Analytics and Predictive Modeling Approaches for the Energy Sector. BigData Congress (2019)
Roberto Corizzo, Michelangelo Ceci, Nathalie Japkowicz
Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data. Big Data Res. 16 (2019)
Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz
Deep Learning Versus Conventional Learning in Data Streams with Concept Drifts. ICMLA (2019)
Domenico Redavid, Roberto Corizzo, Donato Malerba
An OWL Ontology for Supporting Semantic Services in Big Data Platforms. BigData Congress (2018)
Michelangelo Ceci, Roberto Corizzo, Fabio Fumarola, Donato Malerba, Aleksandra Rashkovska
Predictive Modeling of PV Energy Production: How to Set Up the Learning Task for a Better Prediction? IEEE Trans. Ind. Informatics 13 (3) (2017)
Roberto Corizzo, Gianvito Pio, Michelangelo Ceci, Donato Malerba
Forecasting via Distributed Density-Based Clustering. SEBD (2017)
Michelangelo Ceci, Roberto Corizzo, Fabio Fumarola, Michele Ianni, Donato Malerba, Gaspare Maria, Elio Masciari, Marco Oliverio, Aleksandra Rashkovska
Big Data Techniques For Supporting Accurate Predictions of Energy Production From Renewable Sources. IDEAS (2015)
Michelangelo Ceci, Roberto Corizzo, Fabio Fumarola, Michele Ianni, Donato Malerba, Gaspare Maria, Elio Masciari, Marco Oliverio, Aleksandra Rashkovska
VIPOC Project Research Summary (Discussion Paper). SEBD (2015)
Michelangelo Ceci, Nunziato Cassavia, Roberto Corizzo, Pietro Dicosta, Donato Malerba, Gaspare Maria, Elio Masciari, Camillo Pastura
Innovative power operating center management exploiting big data techniques. IDEAS (2014)
Michelangelo Ceci, Nunziato Cassavia, Roberto Corizzo, Pietro Dicosta, Donato Malerba, Gaspare Maria, Elio Masciari, Camillo Pastura
Big Data Techniques For Renewable Energy Market. SEBD (2014)