Zobrazeno 1 - 10
of 21 801
pro vyhledávání: '"Lin, Yang"'
The prediction of disease risk factors can screen vulnerable groups for effective prevention and treatment, so as to reduce their morbidity and mortality. Machine learning has a great demand for high-quality labeling information, and labeling noise i
Externí odkaz:
http://arxiv.org/abs/2406.16982
The 3D simulation model of the lung was established by using the reconstruction method. A computer aided pulmonary nodule detection model was constructed. The process iterates over the images to refine the lung nodule recognition model based on neura
Externí odkaz:
http://arxiv.org/abs/2406.13205
Parameter-efficient fine-tuning methods, represented by LoRA, play an essential role in adapting large-scale pre-trained models to downstream tasks. However, fine-tuning LoRA-series models also faces the risk of overfitting on the training dataset, a
Externí odkaz:
http://arxiv.org/abs/2404.09610
With the increasingly powerful performances and enormous scales of pretrained models, promoting parameter efficiency in fine-tuning has become a crucial need for effective and efficient adaptation to various downstream tasks. One representative line
Externí odkaz:
http://arxiv.org/abs/2404.04316
Autor:
Lin, Yang
In this paper, we introduce ProNet, an novel deep learning approach designed for multi-horizon time series forecasting, adaptively blending autoregressive (AR) and non-autoregressive (NAR) strategies. Our method involves dividing the forecasting hori
Externí odkaz:
http://arxiv.org/abs/2310.19322
Autor:
Lin, Yang
Multi-horizon time series forecasting, crucial across diverse domains, demands high accuracy and speed. While AutoRegressive (AR) models excel in short-term predictions, they suffer speed and error issues as the horizon extends. Non-AutoRegressive (N
Externí odkaz:
http://arxiv.org/abs/2310.19289
Named entity recognition (NER) is a fundamental task in natural language processing that aims to identify and classify named entities in text. However, span-based methods for NER typically assign entity types to text spans, resulting in an imbalanced
Externí odkaz:
http://arxiv.org/abs/2310.18349
Fine-grained entity typing (FET) is an essential task in natural language processing that aims to assign semantic types to entities in text. However, FET poses a major challenge known as the noise labeling problem, whereby current methods rely on est
Externí odkaz:
http://arxiv.org/abs/2310.14596
Integrating optical diffraction tomography with imaging flow cytometry enables label-free quantifications of the three-dimensional (3D) morphology and hemoglobin content of red blood cells (RBCs) in their natural form. Self-rotation of RBCs flowing i
Externí odkaz:
http://arxiv.org/abs/2309.15131
Recently, Andrews proved two conjectures on a partition statistic introduced by Beck. Very recently, Chern established some results on weighted rank and crank moments and proved many Andrews-Beck type congruences. Motivated by Andrews and Chern's wor
Externí odkaz:
http://arxiv.org/abs/2308.05931