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Kamil Faber
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2020 – today
- 2024
- [j4]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. IEEE Access 12: 41364-41380 (2024) - [j3]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo:
From MNIST to ImageNet and back: benchmarking continual curriculum learning. Mach. Learn. 113(10): 8137-8164 (2024) - [c12]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo, Anna Wójcik:
AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework. GECCO Companion 2024: 607-610 - [c11]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
Towards Efficient Deep Autoencoders for Multivariate Time Series Anomaly Detection. ICCS (3) 2024: 461-469 - [i10]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
Towards efficient deep autoencoders for multivariate time series anomaly detection. CoRR abs/2403.02429 (2024) - [i9]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework. CoRR abs/2404.07968 (2024) - 2023
- [j2]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
VLAD: Task-agnostic VAE-based lifelong anomaly detection. Neural Networks 165: 248-273 (2023) - [c10]Kamil Faber, Bartlomiej Sniezynski, Roberto Corizzo:
Distributed Continual Intrusion Detection: A Collaborative Replay Framework. IEEE Big Data 2023: 3255-3263 - [c9]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
Ada-QPacknet - Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning. ECAI 2023: 1882-1889 - [c8]Dominik Zurek, Roberto Corizzo, Michal Karwatowski, Marcin Pietron, Kamil Faber:
Transformed-*: A domain-incremental lifelong learning scenario generation framework. IJCNN 2023: 1-10 - [i8]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
Lifelong Learning for Anomaly Detection: New Challenges, Perspectives, and Insights. CoRR abs/2303.07557 (2023) - [i7]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo:
From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning. CoRR abs/2303.11076 (2023) - [i6]Marcin Pietron, Dominik Zurek, Kamil Faber, Roberto Corizzo:
AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection. CoRR abs/2305.16497 (2023) - [i5]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 abs/2308.07939 (2023) - 2022
- [c7]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 R. Piacentino, Jesse Hostetler, Aswin Raghavan:
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. AIMLSystems 2022: 12:1-12:9 - [c6]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, 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: 1120-1145 - [c5]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz:
Active Lifelong Anomaly Detection with Experience Replay. DSAA 2022: 1-10 - [c4]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
LIFEWATCH: Lifelong Wasserstein Change Point Detection. IJCNN 2022: 1-8 - [i4]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. CoRR abs/2201.07125 (2022) - [i3]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 R. Piacentino, Jesse Hostetler, Aswin Raghavan:
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. CoRR abs/2212.04603 (2022) - 2021
- [j1]Kamil Faber, Marcin Pietron, Dominik Zurek:
Ensemble Neuroevolution-Based Approach for Multivariate Time Series Anomaly Detection. Entropy 23(11): 1466 (2021) - [c3]Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. IEEE BigData 2021: 4450-4459 - [c2]Kamil Faber, Lukasz Faber, Bartlomiej Sniezynski:
Autoencoder-based IDS for cloud and mobile devices. CCGRID 2021: 728-736 - [i2]Kamil Faber, Dominik Zurek, Marcin Pietron, Kamil Pietak:
Ensemble neuroevolution based approach for multivariate time series anomaly detection. CoRR abs/2108.03585 (2021) - [i1]Marcin Pietron, Dominik Zurek, Kamil Faber:
Fast and scalable neuroevolution deep learning architecture search for multivariate anomaly detection. CoRR abs/2112.05640 (2021)
2000 – 2009
- 2009
- [c1]Sergey Kosov, Kristina Scherbaum, Kamil Faber, Thorsten Thormählen, Hans-Peter Seidel:
Rapid stereo-vision enhanced face detection. ICIP 2009: 1221-1224
Coauthor Index
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