Category / Conference
DeepCCI: End-to-end Deep Learning for Chemical-Chemical Interaction Prediction
Near-Data Processing for Differentiable Machine Learning Models
Hyeokjun Choe, Seil Lee, Hyunha Nam, Seongsik Park, Seijoon Kim, Eui-Young Chung, and Sungroh Yoon, in Proceedings of the 33rd International Conference on Massive Storage Systems and Technology (MSST), Santa Clara, USA, May 2017.
Transfer Learning for Deep Learning on Graph-Structured Data
Training IBM Watson using Automatically Generated Question-Answer Pairs
Jangho Lee, Gyuwan Kim, Jaeyoon Yoo, Changwoo Jung, Minseok Kim, and Sungroh Yoon, in Proceedings of the Hawaii International Conference on System Sciences (HICSS), pp. 1683-1691, Waikoloa Village, USA, January 2017.
paper link arXiv
Neural Universal Discrete Denoiser
Taesup Moon, Seonwoo Min, Byunghan Lee, and Sungroh Yoon, in Proceedings of the Thirtieth Annual Conference on Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016.
preprint suppl link
An Efficient Method to Boosting Performance of Spiking Neural Network Training
Seongsik Park, Sang-gil Lee, Hyunha Nam, and Sungroh Yoon, in the Thirtieth Annual Conference on Neural Information Processing Systems (NIPS) Workshop on Computing with Spikes, Barcelona, Spain, December 2016.
paper link arXiv
CloudSocket: Smart Grid Platform for Datacenters
Seil Lee, Hanjoo Kim, Seongsik Park, Seijoon Kim, Hyeokjun Choe, Chang-Sung Jeong, and Sungroh Yoon, in Proceedings of the 34th IEEE International Conference on Computer Design (ICCD), pp. 436-439, Phoenix, USA, October 2016.
deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks
Byunghan Lee, Junghwan Baek, Seunghyun Park, and Sungroh Yoon, in Proceedings of the 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), pp. 434-442, Seattle, USA, October 2016.