5 papers
Source-Free Cross-Domain Continual Learning
Muhammad Tanzil Furqon, Mahardhika Pratama, Igor Å krjanc +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…
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…
PROL : Rehearsal Free Continual Learning in Streaming Data via Prompt Online Learning
M. Anwar Ma'sum, Mahardhika Pratama, Savitha Ramasamy +3
The data privacy constraint in online continual learning (OCL), where the data can be seen only once, complicates the catastrophic forgetting problem in streaming data. A common ap…
Time and Frequency Synergy for Source-Free Time-Series Domain Adaptations
Muhammad Tanzil Furqon, Mahardhika Pratama, Ary Mazharuddin Shiddiqi +3
The issue of source-free time-series domain adaptations still gains scarce research attentions. On the other hand, existing approaches rely solely on time-domain features ignoring…
PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning
Muhammad Anwar Ma'sum, Mahardhika Pratama, Savitha Ramasamy +3
Federated Class Incremental Learning (FCIL) is a new direction in continual learning (CL) for addressing catastrophic forgetting and non-IID data distribution simultaneously. Exist…