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arXiv:2603.00067v1 Announce Type: new Abstract: Medical time-series data are characterized by irregular sampling, high noise levels, missing values, and strong inter-feature dependencies. Recurrent neural networks …
arXiv:2603.00070v1 Announce Type: new Abstract: Standard evaluation metrics for machine learning -- accuracy, precision, recall, and AUROC -- assume that all errors are equivalent: a …
arXiv:2603.00099v1 Announce Type: new Abstract: Neural architecture search (NAS) automates the discovery of neural networks that meet specified criteria, yet its evaluation procedures are often …
arXiv:2603.00101v1 Announce Type: new Abstract: Wideband power amplifiers exhibit complex nonlinear and memory effects that challenge traditional behavioral modeling approaches. This paper proposes a novel …
arXiv:2603.00105v1 Announce Type: new Abstract: Large language models (LLMs) have gained significant attention by many researchers and practitioners in natural language processing (NLP) since the …
arXiv:2603.00137v1 Announce Type: new Abstract: Knowledge tracing (KT) models are commonly evaluated by training on early interactions from all students and testing on later responses. …
arXiv:2603.00176v1 Announce Type: new Abstract: Shared micromobility services such as e-scooters and bikes have become an integral part of urban transportation, yet their efficiency critically …
arXiv:2603.00180v1 Announce Type: new Abstract: Generative modeling of neural network parameters is often tied to architectures because standard parameter representations rely on known weight-matrix dimensions. …
arXiv:2603.00181v1 Announce Type: new Abstract: A recent report on "Learning the natural history of human disease with generative transformers" created an opportunity to assess the …
arXiv:2603.00190v1 Announce Type: new Abstract: Polysomnography (PSG) provides the gold standard for sleep assessment but suffers from substantial heterogeneity across recording devices and cohorts. There …
arXiv:2603.00191v1 Announce Type: new Abstract: Continual Learning (CL) requires models to sequentially adapt to new tasks without forgetting old knowledge. Recently, Low-Rank Adaptation (LoRA), a …
arXiv:2603.00192v1 Announce Type: new Abstract: In healthcare, predictive models increasingly inform patient-level decisions, yet little attention is paid to the variability in individual risk estimates …