5 papers
Hard Cases, Bad Labels: Testing Error Exposure and Error Location in Uncertainty Sampling Under Bounded Label Noise
John Myron Uy
Active learning can reduce labeling cost by selecting informative examples, but the most uncertain examples may also be the hardest to label correctly. This study tests whether unc…
Preventing Latent Rehearsal Decay in Online Continual SSL with SOLAR
Giacomo Cignoni, Simone Magistri, Andrew D. Bagdanov +1
This paper explores Online Continual Self-Supervised Learning (OCSSL), a scenario in which models learn from continuous streams of unlabeled, non-stationary data, where methods typ…
Not All Layers Are Created Equal: Adaptive LoRA Ranks for Personalized Image Generation
Donald Shenaj, Federico Errica, Antonio Carta
Low Rank Adaptation (LoRA) is the de facto fine-tuning strategy to generate personalized images from pre-trained diffusion models. Choosing a good rank is extremely critical, since…
Online Continual Learning for Time Series: a Natural Score-driven Approach
Edoardo Urettini, Daniele Atzeni, Ioanna-Yvonni Tsaknaki +1
Online continual learning (OCL) methods adapt to changing environments without forgetting past knowledge. Similarly, online time series forecasting (OTSF) is a real-world problem w…
Online Curvature-Aware Replay: Leveraging Order Information for Online Continual Learning
Edoardo Urettini, Antonio Carta
Online Continual Learning (OCL) models continuously adapt to nonstationary data streams, usually without task information. These settings are complex and many traditional CL method…