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Haitao Du
Haitao Du
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The objective function of Principal Component Analysis (PCA) is minimizing the reconstruction error in L2 norm (see section 2.12 here. Another view is trying to maximize the variance on projection. We also have an excellent post here: What is the objective function of PCA?).

My question is, that is PCA optimization convex? (I found some discussions here, but wish someone could provide a nice proof here on CV).

The objective function of Principal Component Analysis (PCA) is minimizing the reconstruction error in L2 norm (see section 2.12 here. Another view is trying to maximize the variance on projection. We also have an excellent post here: What is the objective function of PCA?).

My question is, is PCA optimization convex? (I found some discussions here, but wish someone could provide a nice proof here on CV).

The objective function of Principal Component Analysis (PCA) is minimizing the reconstruction error in L2 norm (see section 2.12 here. Another view is trying to maximize the variance on projection. We also have an excellent post here: What is the objective function of PCA?).

My question is that is PCA optimization convex? (I found some discussions here, but wish someone could provide a nice proof here on CV).

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whuber ♦
whuber ♦
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The objective function of PrinciplePrincipal Component Analysis (PCA) is minimizing the reconstruction error in L2 norm (see section 2.12 here. Another view is trying to maximize the variance on projection. We also have an excellent post here: What is the objective function of PCA?).

My question is that, Isis PCA optimization convex? (I found some discussions here, but wish someone cancould provide a nice proof inhere on CV).

The objective function of Principle Component Analysis (PCA) is minimizing the reconstruction error in L2 norm (see section 2.12 here. Another view is trying to maximize the variance on projection. We also have an excellent post here: What is the objective function of PCA?).

My question is that Is PCA optimization convex? (I found some discussions here, but wish someone can provide nice proof in CV)

The objective function of Principal Component Analysis (PCA) is minimizing the reconstruction error in L2 norm (see section 2.12 here. Another view is trying to maximize the variance on projection. We also have an excellent post here: What is the objective function of PCA?).

My question is, is PCA optimization convex? (I found some discussions here, but wish someone could provide a nice proof here on CV).

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Haitao Du
Haitao Du
  • 37.3k
  • 25
  • 148
  • 244

Is PCA optimization convex?

The objective function of Principle Component Analysis (PCA) is minimizing the reconstruction error in L2 norm (see section 2.12 here. Another view is trying to maximize the variance on projection. We also have an excellent post here: What is the objective function of PCA?).

My question is that Is PCA optimization convex? (I found some discussions here, but wish someone can provide nice proof in CV)