Variational few-shot learning for microservice-oriented intrusion detection in distributed industrial IoT
Along with the popularity of the Internet of Things (IoT) techniques with several
computational paradigms, such as cloud and edge computing, microservice has been …
computational paradigms, such as cloud and edge computing, microservice has been …
A survey on learning to reject
Learning to reject is a special kind of self-awareness (the ability to know what you do not
know), which is an essential factor for humans to become smarter. Although machine …
know), which is an essential factor for humans to become smarter. Although machine …
Quality assurance of a GPT-based sentiment analysis system: Adversarial review data generation and detection
Large Language Models (LLMs) have been garnering significant attention of AI researchers,
especially following the widespread popularity of ChatGPT. However, due to LLMs' intricate …
especially following the widespread popularity of ChatGPT. However, due to LLMs' intricate …
Cafa: Class-aware feature alignment for test-time adaptation
Despite recent advancements in deep learning, deep neural networks continue to suffer
from performance degradation when applied to new data that differs from training data. Test …
from performance degradation when applied to new data that differs from training data. Test …
Taxocom: Topic taxonomy completion with hierarchical discovery of novel topic clusters
Topic taxonomies, which represent the latent topic (or category) structure of document
collections, provide valuable knowledge of contents in many applications such as web …
collections, provide valuable knowledge of contents in many applications such as web …
Zero-X: A Blockchain-Enabled Open-Set Federated Learning Framework for Zero-Day Attack Detection in IoV
A Boualouache… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The Internet of Vehicles (IoV) is a crucial technology for Intelligent Transportation Systems
(ITS) that integrates vehicles with the Internet and other entities. The emergence of 5 G and …
(ITS) that integrates vehicles with the Internet and other entities. The emergence of 5 G and …
TVSPrune-pruning non-discriminative filters via total variation separability of intermediate representations without fine tuning
C Murti, T Narshana, C Bhattacharyya - The Eleventh International …, 2023 - openreview.net
Achieving structured, data-free sparsity of deep neural networks (DNNs) remains an open
area of research. In this work, we address the challenge of pruning filters without access to …
area of research. In this work, we address the challenge of pruning filters without access to …
Dual Conditioned Diffusion Models for Out-of-Distribution Detection: Application to Fetal Ultrasound Videos
Abstract Out-of-distribution (OOD) detection is essential to improve the reliability of machine
learning models by detecting samples that do not belong to the training distribution …
learning models by detecting samples that do not belong to the training distribution …
Mitigating viewpoint sensitivity of self-supervised one-class classifiers
Recent studies on one-class classification have achieved a remarkable performance by
employing the self-supervised classifier that predicts the type of pre-defined geometric …
employing the self-supervised classifier that predicts the type of pre-defined geometric …
Anomaly detection via few-shot learning on normality
S Ando, A Yamamoto - Joint European Conference on Machine Learning …, 2022 - Springer
One of the basic ideas for anomaly detection is to describe an enclosing boundary of normal
data in order to identify cases outside as anomalies. In practice, however, normal data can …
data in order to identify cases outside as anomalies. In practice, however, normal data can …