A5102800469- Statistical Methods and Inference
- Imbalanced Data Classification Techniques
- Machine Learning and Data Classification
- CCD and CMOS Imaging Sensors
- Advanced Memory and Neural Computing
- Advanced Neural Network Applications
Vision Transformers (ViTs) mark a revolutionary advance in neural networks with their token mixer's powerful global context capability. However, the pairwise affinity and complex matrix operations limit its deployment on resource-constrained scenarios real-time applications, such as mobile devices, although considerable efforts have been made previous works. In this paper, we introduce CAS-ViT: Convolutional Additive Self-attention Transformers, to achieve balance between efficiency...
Feature importance scores (FIS) estimation is an important problem in many data-intensive applications. Traditional approaches can be divided into two types; model-specific methods and model-agnostic methods. In this work, we present FeatureLTE, a novel learning-based approach to FIS estimation. For the first time, as demonstrate through extensive experiments, it possible build general-purpose pre-trained models for Therefore, reduces prediction outputs from FeatureLTE model. Pre-trained...