This paper introduces SoftEDA, a novel technique that applies soft labels to augmented data. Traditional Easy Data Augmentation (EDA) techniques can potentially damage the original meaning of the text, hurting…
Continue readingThe article delves into the use of graph neural networks (GNN) in dealing with complex relationships and dependencies in graph-structured data. It introduces the concept of graph explanation, which is…
Continue readingThe article discusses the use of deep generative models in offline reinforcement learning and the computational challenges posed by their large model size. To address this, the authors propose a…
Continue readingThe article discusses the use of Raman Spectroscopy in biotechnology as a process analytical technology. It focuses on the use of Convolutional Neural Networks (CNNs) for handling non-Gaussian noise and…
Continue readingThe article introduces a novel approach to Kriging, a method of estimating attributes of unseen locations based on neighboring data. The proposed method, called Contrastive- Prototypical self-supervised learning for Kriging…
Continue readingThe article discusses a framework for training singer identity encoders that can extract representations suitable for singing-related tasks. Different self-supervised learning techniques are explored on a large collection of isolated…
Continue readingThe paper discusses the challenges in automatic recognition of dysarthric speech caused by motor-neuro conditions and physical disabilities. It presents a comparative study of data augmentation approaches to enhance pre-trained…
Continue readingThis research investigates the use of self-supervised learning (SSL) for bird sound classification, particularly in few-shot learning scenarios. The researchers demonstrate that SSL can acquire meaningful representations of bird sounds…
Continue readingThis academic paper discusses the role of data augmentation in improving the transferability of adversarial examples (AEs) in machine learning. The authors systematically studied 46 augmentation techniques and their effects…
Continue readingThe paper presents SUMMaug, a novel approach to data augmentation for document classification. Despite the use of pretrained language models in natural language understanding tasks, comprehending lengthy text remains a…
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