112 citations · 174 across the 13 of their papers we have counts for
7 papers · 1 filter
Sequential Deep Learning Architectures for Anomaly Detection in Virtual Network Function Chains
Chungjun Lee, Jibum Hong, DongNyeong Heo +1
Software-defined networking (SDN) and network function virtualization (NFV) have enabled the efficient provision of network service. However, they also raised new tasks to monitor…
Deep Neural Networks and End-to-End Learning for Audio Compression
Daniela N. Rim, Inseon Jang, Heeyoul Choi
Recent achievements in end-to-end deep learning have encouraged the exploration of tasks dealing with highly structured data with unified deep network models. Having such models fo…
Active Search for Nearest Neighbors
Hayoung Um, Heeyoul Choi
In pattern recognition or machine learning, it is a very fundamental task to find nearest neighbors of a given point. All the methods for the task work basically by comparing the g…
Network Intrusion Detection based on LSTM and Feature Embedding
Hyeokmin Gwon, Chungjun Lee, Rakun Keum +1
Growing number of network devices and services have led to increasing demand for protective measures as hackers launch attacks to paralyze or steal information from victim systems.…
Disentangling Latent Factors of Variational Auto-Encoder with Whitening
Sangchul Hahn, Heeyoul Choi
After deep generative models were successfully applied to image generation tasks, learning disentangled latent variables of data has become a crucial part of deep generative model…
Alpha-Integration Pooling for Convolutional Neural Networks
Hayoung Eom, Heeyoul Choi
Convolutional neural networks (CNNs) have achieved remarkable performance in many applications, especially in image recognition tasks. As a crucial component of CNNs, sub-sampling…
Understanding Dropout as an Optimization Trick
Sangchul Hahn, Heeyoul Choi
As one of standard approaches to train deep neural networks, dropout has been applied to regularize large models to avoid overfitting, and the improvement in performance by dropout…