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1st DELTA 2024: Barcelona, Spain
- Marco Piangerelli

, Bardh Prenkaj, Ylenia Rotalinti, Ananya Joshi, Giovanni Stilo
:
Discovering Drift Phenomena in Evolving Landscapes - First International Workshop, DELTA 2024, Barcelona, Spain, August 26, 2024, Proceedings. Lecture Notes in Computer Science 15013, Springer 2025, ISBN 978-3-031-82345-9
Adaptive and Robust Learning in Dynamic Environments
- Sebastián A. Cajas Ordóñez

, Jaydeep Samanta
, Andrés L. Suárez-Cetrulo
, Ricardo Simon Carbajo
:
Adaptive Machine Learning for Resource-Constrained Environments. 3-19 - Shruti Saxena, Joydeep Chandra:

RoCoNA: A Robust Continual Learning Framework for Alignment of Dynamic Networks Under Distribution Shift and Domain Differences. 20-36 - Jiaqi Guo, Tianpeng Li, Minglai Shao, Wenjun Wang, Lin Pan, Xue Chen, Yueheng Sun:

CeDFormer: Community Enhanced Transformer for Dynamic Network Embedding. 37-53
Challenges and Solutions in Drift Detection and Anomaly Explanation
- Thibault Simonetto

, Maxime Cordy
, Salah Ghamizi
, Yves Le Traon
, Clément Lefebvre, Andrey Boystov, Anne Goujon:
On the Impact of Industrial Delays when Mitigating Distribution Drifts: An Empirical Study on Real-World Financial Systems. 57-73 - Alina Fastowski

, Gjergji Kasneci
:
Understanding Knowledge Drift in LLMs Through Misinformation. 74-85 - Giacomo Ziffer

, Emanuele Della Valle
:
Exploring Concept Drift Visualization and Explanation in Image Streams. 86-98
Innovative Approaches to Concept Drift Detection and Landscape Shifts
- Flavio Giobergia

, Eliana Pastor
, Luca de Alfaro
, Elena Baralis
:
A Synthetic Benchmark to Explore Limitations of Localized Drift Detections. 101-110 - Joanna Komorniczak

, Pawel Ksieniewicz
:
Unsupervised Concept Drift Detection Based on Parallel Activations of Neural Network. 111-127 - Sebastián Basterrech:

Unsupervised Assessment of Landscape Shifts Based on Persistent Entropy and Topological Preservation. 128-145 - Federico Giannini

, Emanuele Della Valle
:
Addressing Temporal Dependence, Concept Drifts, and Forgetting in Data Streams. 146-164

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