Roberto Corizzo

发表

Literature on Applied Machine Learning in Metagenomic Classification: A Scoping Review

N. Garcia, V. Trajkovik, I. Pires, 2020, Biology.

Machine Learning for Surgical Risk Assessment Decision Systems

N. Japkowicz, Roberto Corizzo, D. Russell, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification

B. Krawczyk, N. Japkowicz, C. Bellinger, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

LIFEWATCH: Lifelong Wasserstein Change Point Detection

N. Japkowicz, Roberto Corizzo, B. Sniezynski, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Spatial autocorrelation and entropy for renewable energy forecasting

D. Malerba, Michelangelo Ceci, Roberto Corizzo, 2019, Data Mining and Knowledge Discovery.

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games

Tyler L. Hayes, Mustafa Burak Gurbuz, Sahana P Joshi, 2022, AIMLSystems.

Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data

Michelangelo Ceci, Nathalie Japkowicz, Roberto Corizzo, 2019, Big Data Res..

Innovative power operating center management exploiting big data techniques

Michelangelo Ceci, Donato Malerba, Elio Masciari, 2014, IDEAS.

Big Data Techniques For Renewable Energy Market

Michelangelo Ceci, Donato Malerba, Elio Masciari, 2014, SEBD.

Active Lifelong Anomaly Detection with Experience Replay

N. Japkowicz, Roberto Corizzo, B. Sniezynski, 2022, 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA).

DENCAST: distributed density-based clustering for multi-target regression

Michelangelo Ceci, Donato Malerba, Roberto Corizzo, 2019, Journal of Big Data.

Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification

Eftim Zdravevski, Roberto Corizzo, Petre Lameski, 2020, Sensors.

CPDGA: Change point driven growing auto-encoder for lifelong anomaly detection

N. Japkowicz, Roberto Corizzo, M. Baron, 2022, Knowl. Based Syst..

Big Data Techniques For Supporting Accurate Predictions of Energy Production From Renewable Sources

Michelangelo Ceci, Donato Malerba, Elio Masciari, 2015, IDEAS.

Multi-aspect renewable energy forecasting

Michelangelo Ceci, Hadi Fanaee-T, João Gama, 2021, Inf. Sci..

VLAD: Task-agnostic VAE-based lifelong anomaly detection

N. Japkowicz, Roberto Corizzo, B. Sniezynski, 2023, Neural Networks.

WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data

Nathalie Japkowicz, Roberto Corizzo, Bartlomiej Sniezynski, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets

Michelangelo Ceci, Iluju Kiringa, Nathalie Japkowicz, 2019, Inf. Sci..

Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data

Michelangelo Ceci, Nathalie Japkowicz, Roberto Corizzo, 2021, DS.

Big Data Analytics and Predictive Modeling Approaches for the Energy Sector

Michelangelo Ceci, Donato Malerba, Roberto Corizzo, 2019, 2019 IEEE International Congress on Big Data (BigDataCongress).

DENCAST: distributed density-based clustering for multi-target regression

D. Malerba, Michelangelo Ceci, Gianvito Pio, 2019, Journal of Big Data.

Predictive Modeling of PV Energy Production: How to Set Up the Learning Task for a Better Prediction?

Michelangelo Ceci, Donato Malerba, Roberto Corizzo, 2017, IEEE Transactions on Industrial Informatics.

ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids

Michelangelo Ceci, Nathalie Japkowicz, Roberto Corizzo, 2020, IEEE Access.

Lifelong Learning for Anomaly Detection: New Challenges, Perspectives, and Insights

N. Japkowicz, Roberto Corizzo, B. Sniezynski, 2023, SSRN Electronic Journal.

Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks

Nuno M. Garcia, Ivan Miguel Pires, Eftim Zdravevski, 2020, Remote. Sens..

Feature extraction based on word embedding models for intrusion detection in network traffic

N. Japkowicz, Eftim Zdravevski, Roberto Corizzo, 2020 .

Short-term air pollution forecasting based on environmental factors and deep learning models

Eftim Zdravevski, Roberto Corizzo, Vladimir Trajkovik, 2020, 2020 15th Conference on Computer Science and Information Systems (FedCSIS).

One-Class Learning for AI-Generated Essay Detection

Roberto Corizzo, Sebastian Leal-Arenas, 2023, Applied Sciences.

One-Class Ensembles for Rare Genomic Sequences Identification

Nathalie Japkowicz, Roberto Corizzo, Jonathan Kaufmann, 2020, DS.

Scalable auto-encoders for gravitational waves detection from time series data

Michelangelo Ceci, Nathalie Japkowicz, Eftim Zdravevski, 2020, Expert Syst. Appl..

Transformed-*: A domain-incremental lifelong learning scenario generation framework

Roberto Corizzo, Michał Karwatowski, Kamil Faber, 2023, 2023 International Joint Conference on Neural Networks (IJCNN).

From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning

N. Japkowicz, Antonio Vergari, Roberto Corizzo, 2023, Machine Learning.

Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data

Dong L. Wu, J. Gong, C. Bellinger, 2022, 2022 IEEE International Conference on Big Data (Big Data).

LSTM-based Pulmonary Air Leak Forecasting for Chest Tube Management

N. Japkowicz, S. Gilbert, Roberto Corizzo, 2022, 2022 IEEE International Conference on Big Data (Big Data).

A Deep Fusion Model for Human $vs$. Machine-Generated Essay Classification

Roberto Corizzo, Sebastian Leal-Arenas, 2023, 2023 International Joint Conference on Neural Networks (IJCNN).

Explainable image analysis for decision support in medical healthcare

N. Japkowicz, Eftim Zdravevski, C. Bellinger, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Multi-Horizon Air Pollution Forecasting with Deep Neural Networks

Eftim Zdravevski, Roberto Corizzo, Vladimir Trajkovik, 2021, Sensors.

HURI: Hybrid user risk identification in social networks

N. Japkowicz, Michelangelo Ceci, Gianvito Pio, 2023, World Wide Web.

Deep Learning Versus Conventional Learning in Data Streams with Concept Drifts

Iluju Kiringa, Nathalie Japkowicz, Sid Ryan, 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection

Roberto Corizzo, Kamil Faber, D. Zurek, 2023, ArXiv.

The class imbalance problem in deep learning

B. Krawczyk, N. Japkowicz, Paula Branco, 2022, Machine Learning.

ReMix: Calibrated Resampling for Class Imbalance in Deep learning pdf

Nathalie Japkowicz, Roberto Corizzo, Colin Bellinger, 2020, 2012.02312.

Stock market prediction with time series data and news headlines: a stacking ensemble approach

Roberto Corizzo, Jacob Rosen, 2023, J. Intell. Inf. Syst..

Distributed Continual Intrusion Detection: A Collaborative Replay Framework

Roberto Corizzo, B. Sniezynski, Kamil Faber, 2023, 2023 IEEE International Conference on Big Data (BigData).

Ada-QPacknet - adaptive pruning with bit width reduction as an efficient continual learning method without forgetting

Roberto Corizzo, Kamil Faber, Dominik Zurek, 2023, ArXiv.

Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights

N. Japkowicz, Roberto Corizzo, B. Sniezynski, 2023, IEEE Access.

Aerial Scene Classification through Fine-Tuning with Adaptive Learning Rates and Label Smoothing

Tatjana Atanasova-Pacemska, Eftim Zdravevski, Roberto Corizzo, 2020, Applied Sciences.

Forecasting via Distributed Density-Based Clustering

Michelangelo Ceci, Donato Malerba, Roberto Corizzo, 2017, SEBD.