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cs.LG2025
Source-Free Cross-Domain Continual Learning
Muhammad Tanzil Furqon, Mahardhika Pratama, Igor Škrjanc +3
Although existing cross-domain continual learning approaches successfully address many streaming tasks having domain shifts, they call for a fully labeled source domain hindering t…
cs.LG2025
Black-Box Time-Series Domain Adaptation via Cross-Prompt Foundation Models
M. T. Furqon, Mahardhika Pratama, Igor Skrjanc +3
The black-box domain adaptation (BBDA) topic is developed to address the privacy and security issues where only an application programming interface (API) of the source model is av…
cs.LG2025
Latest Advancements Towards Catastrophic Forgetting under Data Scarcity: A Comprehensive Survey on Few-Shot Class Incremental Learning
M. Anwar Ma'sum, Mahardhika Pratama, Igor Skrjanc
Data scarcity significantly complicates the continual learning problem, i.e., how a deep neural network learns in dynamic environments with very few samples. However, the latest pr…