reference_algs.md

hypothesis testing

test	R^d	1-Graph	1-Grute
1-sample	parametric bootstrap	parametric bootstrap ❓	vertex-MGC ✅
2-sample	MGC ❓	semipar ❓
k-sample	MGC ❓	semipar ❓
independent	MGC ✅

clustering

	low-d	high-d	1-graph	m-graphs	time-series
par	k-m/hclust	k-m	SBM	semipar ❓
semi-par	gmm	IDT ✅	DC-SCM	deltacon ❓
kernel	SC	SC	❓	❓
non-par	❓	❓	robust vertex clustering

SC: spectral clustering. k-m: k-means. IDT: iterative denoising tree

classification

	low-d	high-d	1-graph	m-graphs	time-series
par	LDA	LOL ✅	VN	signal subgraph ❓
semi-par	QDA	QOQ ✅	❓	❓
kernel	SVM	SVM	❓	❓	❓
non-par	RerF ✅	RerF ✅	❓	❓

regression

	low-d	high-d	1-graph	m-graphs	time-series
par	linear	LOL ❓	PLS ❓	❓
semi-par	polynomial	QOQ ❓	❓	❓
kernel	SVR	❓	❓	❓
non-par	RerF ❓	RerF ❓	❓	❓

action/control

	metric
par	discriminability
non-par	MGC-discriminability ❓
non-par	class morphing ❓

low dimensional embedding

	low-d	high-d	1-graph	m-graphs	time-series
par	PCA	PCA	RDPG	joint-embedding ✅	Mr. Sid ✅
semi-par	GMRA ❓	GMRA ❓	HSBM ❓	JOFC ❓	❓
kernel	kernel-PCA	kernal-PCA	❓	❓	❓
non-par	RerF ❓	RerF ❓	❓	❓	❓