112 citations · 174 across the 13 of their papers we have counts for
18 papers
Graph Attention Multi-Agent Fleet Autonomy for Advanced Air Mobility
Malintha Fernando, Ransalu Senanayake, Heeyoul Choi +1
Autonomous mobility is emerging as a new disruptive mode of urban transportation for moving cargo and passengers. However, designing scalable autonomous fleet coordination schemes…
Advanced Scaling Methods for VNF deployment with Reinforcement Learning
Namjin Seo, DongNyeong Heo, Heeyoul Choi
Network function virtualization (NFV) and software-defined network (SDN) have become emerging network paradigms, allowing virtualized network function (VNF) deployment at a low cos…
Partitioning Image Representation in Contrastive Learning
Hyunsub Lee, Heeyoul Choi
In contrastive learning in the image domain, the anchor and positive samples are forced to have as close representations as possible. However, forcing the two samples to have the s…
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…
Adversarial Training with Contrastive Learning in NLP
Daniela N. Rim, DongNyeong Heo, Heeyoul Choi
For years, adversarial training has been extensively studied in natural language processing (NLP) settings. The main goal is to make models robust so that similar inputs derive in…
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…
Reinforcement Learning of Graph Neural Networks for Service Function Chaining
DongNyeong Heo, Doyoung Lee, Hee-Gon Kim +2
In the management of computer network systems, the service function chaining (SFC) modules play an important role by generating efficient paths for network traffic through physical…
Graph Neural Network based Service Function Chaining for Automatic Network Control
DongNyeong Heo, Stanislav Lange, Hee-Gon Kim +1
Software-defined networking (SDN) and the network function virtualization (NFV) led to great developments in software based control technology by decreasing expenditures. Service f…
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.…
Self-Knowledge Distillation in Natural Language Processing
Sangchul Hahn, Heeyoul Choi
Since deep learning became a key player in natural language processing (NLP), many deep learning models have been showing remarkable performances in a variety of NLP tasks, and in…
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…
Persistent Hidden States and Nonlinear Transformation for Long Short-Term Memory
Heeyoul Choi
Recurrent neural networks (RNNs) have been drawing much attention with great success in many applications like speech recognition and neural machine translation. Long short-term me…
Fine-Grained Attention Mechanism for Neural Machine Translation
Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio
Neural machine translation (NMT) has been a new paradigm in machine translation, and the attention mechanism has become the dominant approach with the state-of-the-art records in m…
A Neural Knowledge Language Model
Sungjin Ahn, Heeyoul Choi, Tanel Pärnamaa +1
Current language models have a significant limitation in the ability to encode and decode factual knowledge. This is mainly because they acquire such knowledge from statistical co-…
Context-Dependent Word Representation for Neural Machine Translation
Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio
We first observe a potential weakness of continuous vector representations of symbols in neural machine translation. That is, the continuous vector representation, or a word embedd…