Publications
Synthetic Gradient Methods with Virtual Forward-Backward Networks
ICLR2017 Workshop
Machine Learning / Deep Learning
By : Takeru Miyato, Daisuke Okanohara, Shin-ichi Maeda, Masanori Koyama
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
IEEE TPAMI
Machine Learning / Deep Learning
By : Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Shin Ishii
Distantly Supervised Road Segmentation
Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving in ICCV 2017
By : Satoshi Tsutsui, Tommi Kerola, Shunta Saito
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
ICML 2017
Machine Learning / Deep Learning
By : Seiya Tokui, Issei Sato
Learning Discrete Representations via Information Maximizing Self-Augmented Training
ICML 2017
Machine Learning / Deep Learning
By : Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama
Deep Learning Implementations and Frameworks
AAAI 2017 Tutorial
Machine Learning / Deep Learning
By : Seiya Tokui, Kenta Oono, Atsunori Kanemura
Deep Learning Implementations and Frameworks
PAKDD 2016 Tutorial
Machine Learning / Deep Learning
By : Seiya Tokui, Kenta Oono, Atsunori Kanemura, Toshihiro Kamishima
Testing properties of functions on finite groups
Random Structures & Algorithms 2016, Journal Article
Machine Learning / Deep Learning
By : Kenta Oono, Yuichi Yoshida
Chainer: a Next-Generation Open Source Framework for Deep Learning
Workshop on Machine Learning System in NIPS 2015
Machine Learning / Deep Learning
By : Seiya Tokui, Kenta Oono, Shohei Hido, Justin Clayton
Low-latency Job Scheduling with Preemption for the Development of Deep Learning
OpML 2019
By : Hidehito Yabuuchi, Daisuke Taniwaki, Shingo Omura