手法を比較

	Generative Adversarial Network	サポートベクターマシン（分類）
分野	深層学習	機械学習
系統	Machine learning	Machine learning
提唱年	2014	1995
提唱者	Goodfellow, I. et al.	Cortes, C. & Vapnik, V.
種類	Generative deep learning (adversarial two-network game)	Maximum-margin classifier (kernel method)
原典	Goodfellow, I. et al. (2014). Generative Adversarial Nets. NeurIPS.	Cortes, C. & Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20, 273–297.
別名	Üretici Çekişmeli Ağ (GAN), GAN, generative adversarial nets, adversarial network	Destek Vektör Makinesi (SVM — Sınıflandırma), support-vector network, SVM classifier, maximum-margin classifier
関連	4	5
概要	A Generative Adversarial Network (GAN), introduced by Ian Goodfellow and colleagues in 2014, produces realistic synthetic data through the competition of two neural networks — a generator and a discriminator. It is widely used for image synthesis, data augmentation, and distribution estimation.	The Support Vector Machine, introduced by Corinna Cortes and Vladimir Vapnik in 1995, is a classifier that finds the optimal separating hyperplane between classes in a high-dimensional space. It chooses the boundary that leaves the widest possible margin to the nearest training points, which makes its decisions robust on new data.