380 citations · 1.6k across the 84 of their papers we have counts for
9 papers · 1 filter
Intrinsic Geometric Information Transfer Learning on Multiple Graph-Structured Datasets
Jaekoo Lee, Hyunjae Kim, Jongsun Lee +1
Graphs provide a powerful means for representing complex interactions between entities. Recently, deep learning approaches are emerging for representing and modeling graph-structur…
Training IBM Watson using Automatically Generated Question-Answer Pairs
Jangho Lee, Gyuwan Kim, Jaeyoon Yoo +3
IBM Watson is a cognitive computing system capable of question answering in natural languages. It is believed that IBM Watson can understand large corpora and answer relevant quest…
LSTM-Based System-Call Language Modeling and Robust Ensemble Method for Designing Host-Based Intrusion Detection Systems
Gyuwan Kim, Hayoon Yi, Jangho Lee +2
In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. In this paper, we propose a system-call language-modeling…
An Efficient Approach to Boosting Performance of Deep Spiking Network Training
Seongsik Park, Sang-gil Lee, Hyunha Nam +1
Nowadays deep learning is dominating the field of machine learning with state-of-the-art performance in various application areas. Recently, spiking neural networks (SNNs) have bee…
Near-Data Processing for Differentiable Machine Learning Models
Hyeokjun Choe, Seil Lee, Hyunha Nam +4
Near-data processing (NDP) refers to augmenting memory or storage with processing power. Despite its potential for acceleration computing and reducing power requirements, only limi…
Neural Universal Discrete Denoiser
Taesup Moon, Seonwoo Min, Byunghan Lee +1
We present a new framework of applying deep neural networks (DNN) to devise a universal discrete denoiser. Unlike other approaches that utilize supervised learning for denoising, w…
deepMiRGene: Deep Neural Network based Precursor microRNA Prediction
Seunghyun Park, Seonwoo Min, Hyunsoo Choi +1
Since microRNAs (miRNAs) play a crucial role in post-transcriptional gene regulation, miRNA identification is one of the most essential problems in computational biology. miRNAs ar…
Deep Learning in Bioinformatics
Seonwoo Min, Byunghan Lee, Sungroh Yoon
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced ra…
DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters
Hanjoo Kim, Jaehong Park, Jaehee Jang +1
The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters…